Once reliable pricing models are in place, the cycle moves to enhancing risk management. At this stage, quantitative analysts apply these models to identify, measure, and manage financial risks, such as market risk, credit risk, and liquidity risk. The ability to understand and control risk is crucial for the stability and profitability of trading operations and investment portfolios.

With risks more effectively managed, the next step is to generate alpha, which refers to the development of trading strategies that outperform the market. Quants analyze historical data, apply statistical techniques, and use machine learning models to uncover patterns and inefficiencies that can be exploited for superior returns. These strategies are rigorously backtested and optimized to ensure robustness.

Following the generation of alpha, the process moves to automating trading, where these strategies are translated into algorithms and implemented through automated trading systems. These systems can execute trades at high speed and with precision, allowing firms to take advantage of fleeting market opportunities and reduce the emotional biases of human traders.

The insights gained from automating trades and observing their performance feed into the next phase: driving innovation. In this stage, quantitative researchers explore new financial products, emerging asset classes, and novel modeling techniques. Innovation is key to staying ahead in the competitive landscape of quantitative finance and often leads to the discovery of new pricing inefficiencies, thus restarting the cycle.

This closed-loop system enables continuous refinement and advancement in the field, making the quantitative analysis cycle a cornerstone of modern financial strategies. by chat gpt

In today's rapidly evolving scientific and industrial landscape, certain chemistry-related occupations are experiencing significant growth due to technological innovation, environmental challenges, and increasing demand for specialized expertise. Three key career areas stand out as especially in-demand

1. Analytical Chemists & Materials Scientists
   According to the U.S. Bureau of Labor Statistics (BLS), employment in analytical chemistry and materials science is projected to grow by approximately 6% between 2022 and 2032, outpacing the average growth rate for all occupations (~4%). These professionals play a vital role in developing new materials, ensuring product quality, and conducting advanced chemical analyses across industries such as pharmaceuticals, energy, and manufacturing.

   
   

2. Green Chemistry Specialists
   As global industries shift toward sustainability and climate accountability, green chemistry has emerged as a critical domain. The Royal Society of Chemistry (RSC) reports that the demand for “green skills” in chemistry-related job postings is over eight times higher than the average across all sectors. Green chemistry specialists design environmentally friendly chemical processes and materials, minimizing waste and reducing toxic by-products.

   
   

3. Computational / Digital Chemists & Automation Experts
   With the integration of artificial intelligence, automation, and data analytics into laboratory settings, demand for digital chemists is growing rapidly. The RSC highlights that digital skill requirements in chemistry roles are increasing faster than in other sectors, reflecting the field’s evolution toward smart laboratories and AI-driven experimentation. These experts develop automated workflows, analyze complex data, and improve experimental efficiency through digital tools.

Summary Table

StepDurationMain FocusKey Activities

Bachelor’s | 4 yearsFoundation | Study major courses, join research labs

Master’s | 2 yearsResearch basics | Thesis writing, conference participation

Doctorate | 3–5 yearsAdvanced research | Publish papers, secure grants

Postdoc | 1–3 years (optional)Research strengthening | International research, collaboration

Professor Prep | —Teaching & research prep | Job applications, lecture demos

Professor | IndefiniteTeaching & research | Student mentoring, publications

If you want, I can also suggest recommended universities and labs in Korea or provide tips on how to strengthen each stage! Let me know if you want that.

1. Carbon Capture & Utilization (CCU) Scientist / Engineer
   As climate policies intensify and technological innovation advances, CCU specialists are expected to play a central role in decarbonization strategies. According to OECD and BLS data, carbon capture technologies will drive major transformations in the clean energy workforce.

2. Electrochemical CO₂ Reduction (CO₂RR) Specialist
   As CO₂ electroreduction technologies move toward commercialization, researchers who can convert carbon dioxide into value-added chemicals (such as fuels or feedstocks) are becoming increasingly valuable across academic, industrial, and startup sectors.

3. AI-Driven Automated Synthesis Researcher
   The fusion of artificial intelligence and automation is reshaping laboratory practices. Experts in AI-powered chemical synthesis—often involving robotic platforms—are at the forefront of the next generation of high-throughput and self-driving labs.

ChatGPT의 말:

Sure! Here’s the detailed career roadmap to become a Computer Science professor in Korea, explained step-by-step in English.

Career Roadmap to Become a Computer Science Professor in Korea

Step 1: Bachelor’s Degree (4 years)

• Major: Computer Science, Software Engineering, Information & Communication, or related fields

• Goal: Learn fundamental and applied computer science knowledge

• Preparation:

  • Focus on core courses like programming, data structures, algorithms, and operating systems

  • Gain practical experience through graduation projects or internships

  • Try to join a university research lab early to get research exposure

Step 2: Master’s Degree (2 years)

• Major: Choose a specialized field (e.g., AI, cybersecurity, networks)

• Goal: Learn research methods and write a thesis

• Preparation:

  • Prepare and submit a master’s thesis; try to present at academic conferences

  • Collaborate with your advisor on experiments and projects

  • Attend domestic or international conferences to network

Step 3: Doctoral Degree (Ph.D.) (3–5 years)

• Major: Deepen research in a specialized area chosen during the master’s

• Goal: Develop original research topics and publish multiple papers

• Preparation:

  • Publish papers in SCI-level international journals or prestigious Korean journals

  • Gain experience applying for research grants (national projects, etc.)

  • Present research at conferences and expand your academic network

  • Work as a teaching assistant (TA) to gain teaching experience

Step 4: Postdoctoral Researcher (Optional but Recommended)

• Goal: Strengthen research skills and expand expertise

• Preparation:

  • Conduct postdoctoral research at domestic or overseas universities or institutes

  • Collaborate on various research topics and build teamwork skills

  • Present papers internationally and enhance publication record

Step 5: Prepare for Professor Position

• Preparation:

  • After completing your Ph.D. (and possibly postdoc), apply for open faculty positions at universities

  • Prepare teaching materials such as syllabi and practice mock lectures

  • Highlight research achievements, awards, and grant history

  • Emphasize industry collaboration and successful research funding

Step 6: Professor Life After Hiring

• Role: Teach courses, conduct research, and participate in university administration

• Requirements:

  • Continuously publish research papers and secure funding

  • Mentor and guide students

  • Participate in department and university development activities

1. 신소재 공학자는 무슨 일을 하나요?

신소재 공학자는 금속, 세라믹, 고분자, 반도체, 나노·복합재를 설계·제조·개선하여 더 가볍고 튼튼하며, 전기·열 전도성이 우수하고, 생체 적합성이 뛰어난 ‘새로운 재료 레시피’를 만듭니다. 이 재료들은 스마트폰 칩, 전고체 배터리, 전기차 차체, 인공 뼈, 로켓 부품 등 현대 기술의 핵심에 사용됩니다.

2. 전형적인 업무 흐름

단계핵심 활동대학에서 접하게 될 대표 도구·개념1. 설계과학 데이터와 기본 컴퓨터 모델로 목표 특성을 만족할 원소 조합과 비율을 예측CALPHAD 다이어그램, 기초 양자/DFT 개념, Python 스프레드시트2. 샘플 제작용융, 소결, 코팅(CVD/ALD), 3D 프린팅 등으로 시험편 제작고온로, 클린룸 장비, 3D 프린터3. 시험·분석X-선·전자현미경으로 원자 구조 확인, 기계·전기·열 특성 측정XRD, SEM/TEM, 인장 시험기, 전기화학 셀4. 개선시험 데이터와 예측값 비교 후 재료 조성·공정 조건 미세 조정기초 통계, 데이터 시각화 코딩5. 공정화·품질 관리공장 규모 제조법 개발, 안전·품질 문서 작성, 생산 결함 해결품질 관리(QC) 기초, ISO/ESG 개념

3. 필요한 지식과 역량

영역고등학교 준비대학 이후 심화과학 기초대수·기초 미적분, 화학 결합, 물리(열·전기)재료 열역학, 결정학, 표면과학실험 감각과학 보고서 작성 습관XRD·SEM 등 장비 실습코딩·데이터Python 기초(배열, 간단 그래프)기초 DFT/MD, 재료 데이터 과학·머신러닝소프트 스킬발표·영어 과학 읽기특허·논문 작성, 다학제 팀 프로젝트

4. 학습 경로 예시

1. 고교

   • 수학·물리·화학 집중, 과학 동아리 활동·탐구 프로젝트 참여

   • 내신·논술·수능 등 대학 입시 대비

2. 학사 과정 ― 신소재/재료공학 전공

   • 1·2학년: 재료 과학 기초 이론·실험

   • 3·4학년: 반도체·배터리·세라믹 등 심화 과목 + 캡스톤 프로젝트

3. 대학원 (선택)

   • 배터리, 나노전자, 바이오 소재 등 세부 분야 연구 → R&D 경쟁력 강화

5. 진출 분야와 직무 예

산업직무 예시주요 역할반도체공정·소재 엔지니어2 nm 트랜지스터용 재료 개발배터리전고체 전해질 연구원전기차용 안전·장수 셀 설계항공우주초고내열 세라믹 엔지니어로켓 노즐·엔진 부품 소재자동차경량 합금 엔지니어전기차 차체 중량 30 % 감소의료생체재료 개발자3D 프린트 뼈·피부 임플란트국책 연구소재료 분석가국가 소재 표준·데이터 구축

6. 전망 & 핵심 메시지

• 수요가 왜 클까? 반도체·배터리 ‘슈퍼사이클’, 그린 에너지, 우주 탐사, 맞춤형 의료 등에서 첨단 소재가 필수이지만 전문가가 부족합니다.

• 결론 : 화학과 물리를 좋아하고 ‘물질의 DNA’를 새로 쓰고 싶다면, 신소재 공학자는 미래 경쟁력이 매우 높은 진로입니다.

Materials (Advanced) Engineer — High-School Friendly Overview

1. What Does a Materials Engineer Do?

A materials engineer designs, makes, and improves metals, ceramics, polymers, semiconductors, nano- and composite materials so that they become lighter, stronger, more conductive, or more biocompatible. These “new recipes” power things like phone chips, solid-state batteries, electric-car frames, artificial bones, and rocket parts.

2. Typical Work Flow

StepCore ActionsKey Tools / Ideas youʼll meet in college1. DesignUse science data and basic computer models to predict which elements (and how much of each) will give the target property.CALPHAD charts, intro quantum/DFT ideas, Python spreadsheets2. Make SamplesMelt, sinter, coat (CVD/ALD), or 3-D-print tiny test pieces.Furnaces, clean-room gear, 3-D printers3. Test & AnalyzeCheck the atomic structure (X-ray, electron microscopes) and measure mechanical, electrical, or thermal performance.XRD, SEM/TEM, tensile tester, simple electrochemistry cells4. ImproveCompare test data with predictions and tweak the recipe or processing conditions.Basic statistics, coding for data plots5. Scale-Up & QualityDevelop a factory-ready process, write safety/quality documents, and solve defects on production lines.Quality-control basics, ISO/ESG ideas

3. Skills & Knowledge You’ll Need

AreaHigh-School PrepCollege / BeyondScience CoreStrong algebra, calculus basics, chemistry bonding, physics (heat, electricity).Materials thermodynamics, crystallography, surface scienceLab SenseWrite clear lab reports in science classes.Instrument labs: XRD, SEM, thermal analysisCoding & DataPython basics (arrays, simple plots).Intro DFT/MD sims, data science / machine-learning for materialsSoft SkillsOral presentations, English science reading.Patent writing, teamwork with other engineering majors

4. Study Path Example

1. High School – Focus on math, physics, chemistry; join a science club or research project; keep grades high for admissions or essay exams.

2. Bachelor’s Degree – Major in Materials Science/Engineering (first two years: fundamentals; last two years: semiconductor, battery, or ceramics electives + capstone project).

3. Master’s/Ph.D. (optional but valuable for R&D) – Specialize in batteries, nano-electronics, biomedical materials, etc.

5. Where Can You Work?

IndustryExample RoleSimple MissionSemiconductorsProcess or materials engineerBuild 2 nm transistor materialsBatteriesSolid-state electrolyte researcherSafer, longer-life EV cellsAerospaceUltra-high-temp ceramics engineerRocket engine nozzlesAutomotiveLightweight alloy engineerCut EV body weight 30 %BiomedicalBiomaterial developer3-D-printed bone/skin implantsNational LabsMaterials analystSet national standards, publish data

6. Outlook & Take-Away

• Why in demand? Chip and battery “super-cycles,” green energy, space exploration, and personalized medicine all need cutting-edge materials—and there aren’t enough experts yet.

• Bottom line: If you enjoy chemistry and physics and want to “rewrite the DNA of matter,” becoming a materials engineer is a future-proof career worth pursuing.

Chatgpt says : Yes, Computer Science Professors will definitely exist in 2035 and beyond. Here’s why:

Why Computer Science Professors Will Still Exist in 2035

1. Ongoing Technology Growth

   • Technology is constantly evolving (AI, quantum computing, cybersecurity, etc.).

   • Universities need experts to teach new knowledge and conduct research.

2. Need for Education and Research

   • Training the next generation of tech professionals requires skilled educators.

   • Research advances depend heavily on university labs and professors.

3. Human Guidance and Mentorship

   • Professors provide personalized mentorship and critical thinking skills that AI can’t fully replace.

   • Ethical and societal discussions around tech require human insight.

4. New Fields and Interdisciplinary Areas

   • Emerging topics like AI ethics, data privacy, human-computer interaction will grow.

   • Professors will lead these new research and teaching fields.

In short:

• While teaching methods may evolve with AI and technology, the role of a Computer Science Professor as a researcher, mentor, and knowledge creator will remain essential in 2035.

1. Interdisciplinary Knowledge

   • Ability to integrate chemistry with fields such as AI, data science, materials engineering, and environmental policy.

   • "Tomorrow’s chemists must think beyond the lab bench."

2. Digital & Data Literacy

   • Proficiency in coding (e.g., Python, MATLAB), handling large datasets, and using digital lab tools.

   • Understanding of AI-driven tools and automation systems is a growing necessity.

3. Problem-Solving & Innovation Mindset

   • Capacity to design creative solutions for complex sustainability challenges like carbon capture, energy conversion, and circular chemistry.

   • Willingness to experiment, iterate, and adapt.

4. Communication & Collaboration

   • Strong verbal, written, and visual communication skills.

   • Ability to work across diverse, often global, interdisciplinary teams.

5. Adaptability & Lifelong Learning

   • In fast-evolving fields, learning new tools, methods, or regulations is essential.

   • A growth mindset ensures long-term relevance and career mobility.

Please list and describe physics-related careers that are considered socially important and influential for each of the years 2025 and 2035, separately. For each career, explain what makes it important and what kinds of societal needs or challenges it helps address (e.g., climate change, health care, energy systems, AI integration, space exploration).

Then, compare the careers from 2025 and 2035:

• Which careers gained importance over time, and why?

• Which careers became less emphasized, and what changed?

• Analyze the reasons for these changes in terms of social, technological, or environmental trends.

Make sure your analysis includes careers related to energy systems, medical technology, space and satellite technology, AI-physics convergence, and sustainability if relevant.

Use clear structure and explanations suitable for a science-focused high school student audience.

“Have you ever imagined a CEO who designs eco-friendly materials, manages global teams, and leads innovation from the lab to the market? That’s me in 2035.”

미래 직업 소개: 나는 친환경 소재 개발 스타트업의 CEO가 되어, 화학 기술을 이용해 환경 문제를 해결하는 데 기여할 것이다.

이 직업이 중요한 이유: 환경 위기와 에너지 전환 시대, 기술을 이해하고 이끌 수 있는 CEO가 더 중요해지고 있다.

미래 전망: ‘Tech CEO’ 중 이공계 출신 비율이 증가 중이며, 특히 지속가능성과 화학·소재 관련 산업은 급성장 중이다.

2. 본론 (1.5~2분)

단계 1: 교육과 전공

화학공학 전공, 경영학 부전공

환경화학, 재료공학, 사업개발 관련 과목 이수

영어 외에 제2외국어(중국어/스페인어)로 글로벌 커뮤니케이션 능력 확보

단계 2: 경험과 기술

대학 시절 연구 프로젝트 참여 (예: 친환경 플라스틱 개발)

인턴십: LG화학, 한화솔루션 등에서 실무 경험

창업 동아리 및 공모전 참여 → 비즈니스 모델링 경험

생산 공정, 경영분석, 팀 리더십 훈련 병행

단계 3: 리더십과 네트워킹

멘토링 프로그램 참여 (현직 CEO/CTO 멘토 매칭)

TED 발표 연습, 커뮤니케이션 능력 향상

초기 창업 아이디어를 엑셀러레이터에 피칭, 실현력 검증

3. 결론 (20~30초)

“By combining science with leadership, and engineering with business, I’ll lead a company that changes the world – not just with ideas, but with real products that solve real problems.”

핵심 요약: 화학공학 전공을 통해 기술적 기반을 다지고, 사업 경험과 리더십 역량을 쌓아 CEO의 꿈을 실현하겠다는 계획

🎯 Goal: Get accepted to POSTECH and build your science/tech foundation.

📚 Focus Subjects

• Math: Calculus, linear algebra, probability & statistics

• Physics: Strong understanding of modern/quantum physics

• CS: Learn Python and basic algorithmic thinking

🛠 Skills to Build

• 🧠 Python programming (basic → OOP → data science)

• 🧪 Read beginner-friendly quantum concepts (e.g. superposition, entanglement)

• 🤖 Try basic ML projects (like image classification)

🎓 Preparation for POSTECH

• Take top grades in math, physics, and informatics

• Prepare for:

  • portfolio: research etc.

  • emphasize future goal → “Quantum AI”

• Activities:

  • participate in KOI

  • Personal research (e.g. Qiskit project on qubit gates)

  • Join science/maker clubs

  • TOEFL (aim 105+), SAT optional

🟧 Phase 2: POSTECH (Bachelor’s)

🎯 Goal: Master fundamentals of AI + Quantum, prepare for Caltech grad school.

🧑‍🎓 Recommended Majors/Tracks

• Major in Physics or Electrical Engineering

• Minor or double major in Computer Science

📚 Core Courses to Take

• Linear Algebra, Differential Equations, Probability

• Quantum Mechanics I & II

• Algorithms and Data Structures

• Machine Learning, Deep Learning

• Quantum Computing (check for research labs or custom projects)

🧪 Research & Projects

• Use Qiskit, PennyLane, Cirq for quantum simulation

• Build hybrid quantum-classical ML models

• Do undergraduate research (UROP, Lab Internships)

• Work with POSTECH professors doing quantum or AI work

🌎 Global Exposure

• Apply for POSTECH exchange programs or summer research at Caltech (SURF Program)

• Join international competitions or hackathons

• Prepare for GRE (if required), TOEFL (110+), and strong academic references

🟩 Phase 3: Caltech (Master’s/PhD)

🎯 Goal: Deep research in Quantum Machine Learning and publish in top journals.

🧑‍🔬 Caltech Programs to Target

• PhD in Physics, Computer Science, or Quantum Information Science

• Focus Areas:

  • Quantum Algorithms

  • Quantum-enhanced Machine Learning

  • Hybrid Quantum-Classical Neural Networks

📚 Courses & Labs

• Quantum Information and Computation (John Preskill’s area)

• Applied Physics Lab

• Center for Quantum Information and Matter (CQIM)

🧪 Research & Collaboration

• Write and publish research papers

• Attend conferences (QCE, NeurIPS, QIP)

• Collaborate with Google Quantum AI or NASA labs nearby

🟦 Phase 4: Career as Quantum AI Engineer

🎯 Goal: Work in top-tier quantum/AI research or tech companies

🔍 Target Companies

• Google Quantum AI (Sycamore team)

• IBM Quantum (Qiskit, superconducting qubits)

• Xanadu (Quantum + ML pioneer)

• Microsoft Quantum (Topological Qubits)

• Research Institutes (Caltech, NASA QCI, CERN QML)

💼 Role Examples

• Quantum Software Engineer

• Quantum + AI Researcher

• Quantum Algorithm Developer

• Hybrid Model Architect

• Teaches undergraduate and graduate chemistry students at a university and conducts research, manages a lab, supervises theses.

• Requires Ph.D. followed by academic appointments: Assistant → Associate → Full Professor.

• Projected salary by 2035 in South Korea: around ₩90M–₩110M as a starting annual income, with additional incentives for research achievements webzine.mynewsletter.co.kr.

2. Science Communicator (Side Role)

• Creates accessible chemistry and research content via YouTube, podcasts, or blogs.

• Operates media channels in spare time while working as a professor—e.g., experiment demos, research vlogs.

• Enhances public science literacy and strengthens the professor’s personal brand.

  
  

  -Pathway to Achieving These Roles

1. Bachelor’s → Master’s/Ph.D.
   – Study chemistry, build research experience through graduate programs.

2. Secure Academic Credentials
   – Publish in journals, present at conferences, gain teaching experience (e.g., TA).

3. Obtain Faculty Position
   – Start as Assistant Professor, progress with proven research and teaching track record.

4. Launch Science Communication Activities
   – Start a science media channel in spare time (YouTube, podcast, etc.).

   
   

   - 2035 Outlook (Significance & Outlook)

• Social Importance: Key role in chemical industry, environment, and new material research.

• Digital education trend increases the need for accessible science communication.

• Higher Salary Potential: Performance-based incentives and government-funded research support.

• Communication Activities Benefit: Boosts reputation, opens opportunities for public lectures and writing.

-'the job I chose is, pioneer of past, Paleogeologist.'

-Paleogeologist

-The job outlook for paleogeologists is strong, with growing demand in climate and resource exploration.

-It's cool to explore Earth's past

Body

-Study paleogeology or geology at a university, typically for 4-6 years (bachelor’s to master’s).

-Gain experience through internships at research institutes and certifications in GIS, data analysis.

-Seek mentorship from academic advisors, stay motivated by focusing on climate impact, and overcome challenges with resilience

Conclusion

-Become a paleogeologist by studying geology, interning, earning GIS certifications, and networking with mentors.

Intro

Attention grabber: YouTube, Netflix, Amazon use machine learning

What is your future job: Machine Learning Engineer

How available will this job be in the future: increasing bills, used in various industries

Why does it matter: can change the world, can predict the future, one of the promising jod these days

Body

How will you achieve this goal? Make 2-3 clear points

Education: 

1.Bachelor’s Degree? (4 years)

  I will start by earning a Bachelor’s degree in Computer Science, Data Science, or a related field.
In this program, I’ll study mathematics (like calculus and linear algebra), programming (Python, C++), and machine learning basics. This will build a strong foundation in both theory and practical skills.

2.Master’s Degree? (2 years)

   After my undergraduate studies, I plan to earn a Master’s degree in Artificial Intelligence or Machine Learning.

Here, I’ll go deeper into topics like deep learning, natural language processing, and computer vision, and work on real-world projects or research. This advanced degree will increase my job opportunities and help me stand out in a competitive field.

3.Doctorate? (3-6 years)

  While studying, I will build hands-on experience through:

• Internships at tech companies
  
  

• Personal projects (e.g., building ML models with Python, Kaggle competitions)
  
  

• Using tools like TensorFlow, PyTorch, and scikit-learn
  
  

I will also stay connected to the tech community through networking, online forums, and conferences, and always keep learning — because AI and ML are constantly evolving.

Experience & skills: 

To succeed as a Machine Learning Engineer, I will:

• Develop strong coding skills in Python, R, and SQL
  
  

• Practice building and deploying machine learning models
  
  

• Study and apply statistics, algorithms, and optimization techniques
  
  

• Learn how to work with real-world data, clean it, and use it effectively
  
  

These skills will be developed through university projects, personal challenges, internships, and online learning platforms like Coursera and edX.

Networking & Mindsets:

I’ll grow my professional network by:

• Joining tech communities, LinkedIn groups, and local meetups
  
  

• Participating in AI conferences, workshops, and hackathons
  
  

At the same time, I’ll keep a growth mindset — staying curious, being open to feedback, and never stopping learning. This mindset will help me adapt to new technologies and overcome challenges in the field.

Conclusion

Summarize my goal and key points

In conclusion, my goal is to become a Machine Learning Engineer — someone who creates intelligent systems that learn and improve from data.
To achieve this, I will:

1. Study deeply through a Bachelor’s and possibly Master’s or Doctorate degree,
   
   

2. Gain experience by working on projects, internships, and using real tools,
   
   

3. Build strong skills and connections, and keep a mindset of lifelong learning.
   
   

With hard work and passion, I believe I can shape the future through machine learning.

1. Machine Learning Engineer

Uses advanced math and algorithms to build AI systems that learn from data.

Strong in: linear algebra, calculus, probability, and statistics.

2. Data Scientist

Analyzes complex data to find patterns and support decision-making in business, health, finance, and more.

Strong in: statistics, programming, and data modeling.

3. Quantitative Analyst (Quant)

Works in finance to build models for trading, risk analysis, and investment strategies.

Strong in: stochastic calculus, linear algebra, and financial math.

4. Actuary

Assesses risk using probability and statistics, often in insurance or finance.

Strong in: actuarial science, statistics, and risk theory.

5. AI Research Scientist

Creates new machine learning algorithms and explores deep AI theory.

Strong in: pure math, statistics, optimization, and logic.

6. Cryptographer / Cybersecurity Analyst

Uses number theory and algebra to develop secure communication systems.

Strong in: discrete math, abstract algebra, and cryptography.

7. Operations Research Analyst

Solves optimization problems in logistics, transportation, or business using mathematical models.

Strong in: linear programming, optimization, and decision theory.

Intro

• Attention grabber: show Faker and Tourist.

• Basic skill is important

• and computer science is basic skill of today's computer field

• so I want to be computer science professor, and learn many about computer science.

Body

• step1. high school

  • studying hard with science&math subject

  • learning about Computer Science and algorithm with baekjoon, codeforce, atcoder, participating in algorithm competition like KOI, IOI etc.

  • joining CS club

  • ready for colleges with computer science

    • KAIST, SNU, MIT, Georgia Tech, Stanford University, etc..

• step2. Bachelor degree & Master degree

  • Completing undergraduate courses(Math, Science, Computer Science etc..)

  • participating in algorithm competition like UCPC, Cordeforce(online competition site)

  • selecting my certain field, making new paper for Master degree and making new web sites or app (portfolio)

• step3. PhD and Beyond

  • making paper many many

  • learning my field deeply

  • and becoming Professor and educating students

Conclusion

• I want to be the professor with Computer Science

• so i'm learning about Computer Science and will learn about Computer Science

• with that rodemap!!

Attention Grabber:

"Imagine designing the next generation of aircraft and spacecraft that will revolutionize how we travel and explore the universe."

Future Job:

My dream is to become an aerospace engineer.

Job Outlook (Statistics):

Why It Matters to Me:

I am passionate about flight and space technology, and I want to contribute to innovations that expand human exploration and national capabilities.

2. Body (1.5–2 minutes)

How I Will Achieve This Goal

1. Education: Bachelor’s, Master’s and Doctoral Degree at Top Korean Universities

I plan to study in the Department of Aerospace Engineering at one of Korea’s leading science and technology universities:

KAIST (Korea Advanced Institute of Science and Technology):

Renowned for its Department of Aerospace Engineering, offering strong theoretical and hands-on training in aerodynamics, propulsion, and system design.

POSTECH (Pohang University of Science and Technology):

The Department of Mechanical Engineering offers aerospace-related courses and research opportunities.

UNIST (Ulsan National Institute of Science and Technology):

Known for innovative engineering programs and global research collaborations.

I will complete a 4-year bachelor’s degree and a 1–2 year master’s degree to build advanced expertise. I plan to spend 1-2 years focusing on study and research to earn my doctoral degree. Through this, I hope to develop deeper expertise in a more specialized field.

2. Experience & Skills

I will pursue internships and research opportunities at leading aerospace organizations:

KARI (Korea Aerospace Research Institute):

Korea’s national aerospace R&D center, leading projects in satellites, rockets, and space exploration.

Hanwha Aerospace:

A major industry player specializing in aircraft engines, propulsion systems, and defense aerospace technologies.

I will participate in university research labs, join aerospace clubs, and earn certifications (e.g., CAD software) to strengthen my technical skills.

3. Networking & Mindset

I will seek mentorship from professors and industry professionals at KAIST, POSTECH, and UNIST, as well as from experts at KARI and Hanwha.

Staying motivated, setting clear goals, and developing resilience will help me overcome challenges and keep up with rapid technological advancements.

3. Conclusion (20-30 seconds)

Summary:

My goal is to become an aerospace engineer by studying in the Department of Aerospace Engineering at KAIST, POSTECH, or UNIST, completing bachelor’s, master’s and doctoral degrees, gaining hands-on experience at KARI and Hanwha, and building a strong professional network.

Final Thought:

With focused education and real-world experience, I am confident I will contribute to the future of aerospace technology and innovation, helping Korea reach new heights in the global aerospace industry.

1. Attention Grabber

Have you ever thought about how governments make big decisions — like raising interest rates or changing tax systems?

What if those choices could be made smarter, using data?

2. What is your future job, and what does it do?

In 2035, I hope to become a Big Data Analyst for Economic Policy.

This job involves collecting and analyzing large-scale economic data — such as spending trends, employment patterns, and consumer behavior — to help governments make better financial decisions.

3. How available will this job be in the future?

As global economies become more complex and data-driven, this job will become even more essential.

Governments and financial institutions already rely on data analysts to manage crises, predict inflation, and plan budgets.

In the future, real-time data analysis will guide fast, accurate, and evidence-based policymaking.

4. Why does it matter to you?

I care about how decisions affect people’s lives — like job markets, housing prices, or public welfare.

This career allows me to combine my love for economics and statistics, and make a real impact on national and global scales.

Body

1. Education – What will you study? Where? For how long?

I plan to major in Economics or Data Science, possibly at Seoul National University or an international school like LSE.

I’ll study topics like statistics, machine learning, and economic theory for 4 years, and consider graduate research in public policy analytics.

2. Experience & Skills – How will you gain practical knowledge?

I’ll intern at think tanks like KDI or global organizations such as the OECD or IMF.

There, I’ll learn how to work with large datasets, economic models, and policy simulations.

I’ll also practice coding in Python, R, and use tools like Tableau or SQL.

3. Networking & Mindset – How will you grow professionally and stay motivated?

I’ll attend data science forums and policy conferences, and learn from professionals in government and academia.

Even when the data is unclear or complex, I’ll stay focused — because better analysis means better lives for real people.

Conclusion

Becoming a Big Data Analyst for Economic Policy is my dream job.

It combines my passion for numbers and my desire to improve society.

With sharp thinking, strong data skills, and a heart for public service, I hope to guide smarter decisions — and help shape a better future.

1. Attention Grabber

What if we could create materials stronger than steel, lighter than plastic, and even smarter than we are?

2. What is your future job, and what does it do?

My dream job is to become a New Materials Scientist in Chemistry.

I will design and develop advanced materials with special properties — for example, self-healing coatings, flexible batteries, or eco-friendly packaging.

3. How available will this job be in the future?

As industries grow more high-tech and eco-conscious, new materials are in high demand.

Fields like aerospace, medicine, and clean energy all need innovation in materials.

4. Why does it matter to you?

I love chemistry and want to solve real problems like pollution and resource waste.

Creating smart, sustainable materials is my way to make a difference.

🔹 Body

1. Education – What will you study? Where? For how long?

I’ll major in Chemical Engineering or Materials Science at a top university for 4 years, and possibly continue with graduate research.

2. Experience & Skills – How will you gain practical knowledge?

I’ll join lab projects and internships at research centers like KIST or LG Chem.

I’ll learn lab techniques, nanotech tools, and data analysis.

3. Networking & Mindset – How will you grow professionally and stay motivated?

I’ll connect with scientists, attend innovation forums, and keep learning from every experiment — even failures.

🔹 Conclusion

Becoming a new materials scientist is not just my goal — it’s my mission.

With creativity, chemistry, and commitment, I want to build the materials of the future.

1. Attention Grabber

Have you ever wondered what secrets are hidden beneath the surface of distant planets?

2. What is your future job, and what does it do?

My future job is to become a Planetary Data Analyst.

A planetary data analyst studies planets using satellite and space mission data.

They look for patterns in temperature, atmosphere, and surface activity to understand a planet’s history and environment.

3. How available will this job be in the future?

With more missions to the Moon, Mars, and exoplanets, the demand for data experts in space science is growing fast.

Organizations like NASA, ESA, and private space companies need analysts to make sense of the massive data they collect.

This role will be even more essential in 2035, as planetary exploration becomes more advanced.

4. Why does it matter to you?

I was interested in planets and space, and at the same time, I wanted to try solving problems through programming.

This job is a perfect combination of my passions — it lets me explore other worlds through data, not just imagination.

And someday, my analysis might even support the search for life beyond Earth.

Body

1. Education – What will you study? Where? For how long?

To prepare, I’ll major in Astronomy or Data Science at a top university like KAIST or an international school like MIT.

I’ll study for four years as an undergraduate and consider a master’s degree in planetary science or astrophysics.

2. Experience & Skills – How will you gain practical knowledge?

I plan to join research programs at KASI and apply for internships related to space missions.

I’ll learn Python, machine learning, and how to process real satellite data.

I may also participate in global science challenges or hackathons focused on space analytics.

3. Networking & Mindset – How will you grow professionally and stay motivated?

I’ll connect with professors and scientists who work in this field.

To stay inspired, I’ll attend conferences, join online research groups, and always be open to learning new methods.

When challenges come, I’ll remind myself: planets take millions of years to form — and true growth takes time, too.

Conclusion

Becoming a Planetary Data Analyst is my dream job.

It connects my curiosity for planets with my love of science and technology.

To achieve this goal, I’ll focus on education, practical experience, and a strong learning mindset.

With patience, passion, and purpose, I believe I can uncover the hidden stories of planets — not just by watching the skies, but by decoding the data.

In the future, I want to become an applied mathematician.

This job uses math to solve real-world problems, like climate change, finance, artificial intelligence, and health care.

As data and technology become more important, math will be needed even more.

That’s why I think this job has a bright future.

Math isn’t just about numbers to me.

It’s a tool to understand the world and make better decisions.

I enjoy finding patterns, solving hard problems, and thinking logically.

So this job feels right for me.

Body

To reach this goal, I plan to study math or applied math in college.

I’ll learn subjects like calculus, linear algebra, and statistics.

If needed, I want to go on to a master’s or even a PhD, to study more deeply and do research.

But just learning in class isn’t enough.

I also want to gain real experience.

In high school, I can join math clubs or camps, and learn to code with Python.

That way, I can practice using math to solve problems.

In college, I hope to join research programs or internships.

For example, working on projects about data analysis or math models in science or economics.

This will help me understand how math is used in the real world.

Another important step is learning from mentors.

I want to ask questions, listen to advice, and grow from my mistakes.

Even when things are difficult, I’ll try to keep going and keep learning.

Conclusion

In 2035, I hope to be an applied mathematician

who uses math to understand complex problems and help others.

To get there, I’m starting now—by learning math, building skills, and exploring how math connects to the real world.

It won’t be easy, but I believe that math can truly make a difference,

and I want to be part of that change.

Have you ever wondered what the universe is really made of?

Not just atoms or molecules — but the tiniest, invisible particles that build our entire world?

In 2035, I dream of becoming a Particle Physicist — someone who studies the smallest building blocks of matter and energy.

We’re not just studying particles — we’re asking questions like:

Why does the universe exist? What lies beyond what we can see?

Through quantum mechanics and high-energy physics, particle physicists challenge what we know and open the door to new realities.

It’s not just science — it’s the foundation of how we understand everything.

Right now, I’m a student at a science high school in Korea.

I plan to take advanced physics, enter science competitions, and attend summer research programs in quantum and particle physics.

In university, I’ll major in Physics, focusing on quantum theory and high-energy systems.

Then, I plan to enter KAIST Graduate School, where I’ll specialize in theoretical or experimental particle physics.

During my Ph.D., I want to work on long-term projects — like analyzing collision data, exploring new particles, or using deep learning to improve detector systems.

I also hope to publish first-author papers in journals like Physical Review D or JHEP, and present at international conferences like ICHEP or EPS-HEP.

While in grad school, I want to collaborate with global labs such as CERN or Fermilab.

These experiences will prepare me for a postdoctoral position or a full-time research role at a leading institute.

Becoming a particle physicist isn’t just about solving equations.

It’s about staying curious, thinking big, and never being afraid to ask, “What if?”

In the end, I don’t just want to study particles — I want to rethink the foundations of our universe.

With knowledge, collaboration, and bold ideas, I hope to open up a new world of understanding for future generations.

Thank you.

As the fields of quantum computing and artificial intelligence continue to rapidly evolve, the job landscape in Quantum AI is expected to transform significantly by 2035. It is essential to investigate which roles will be the most impactful and in-demand in this interdisciplinary scientific field.

By 2035, several specialized positions are projected to be critical in advancing technology and solving complex problems. These roles may include:

• Quantum Machine Learning Researcher: Experts who develop new algorithms combining quantum computing with AI techniques to enhance data analysis, optimization, and pattern recognition beyond classical capabilities.

• Quantum Software Engineer: Professionals responsible for designing, implementing, and optimizing software for quantum processors, creating tools and libraries that enable hybrid classical-quantum applications.

• Quantum Algorithm Developer: Scientists who invent and refine algorithms tailored for quantum computers to solve specific problems in fields like cryptography, materials science, and drug discovery.

• Hybrid Quantum-Classical Systems Architect: Specialists who integrate quantum processors with classical computing infrastructures to maximize performance and scalability in real-world applications.

• Quantum Data Scientist: Analysts who apply quantum-enhanced machine learning methods to interpret complex datasets in sectors such as finance, healthcare, and logistics.

• Quantum Cybersecurity Analyst: Experts focused on developing post-quantum cryptographic systems and securing quantum communication networks.

These jobs represent a convergence of physics, computer science, and mathematics, requiring a deep understanding of both quantum mechanics and AI principles.

2. Essential Skillsets, Educational Background, and Certifications

To succeed in these emerging roles, individuals will need a robust combination of skills and formal education, coupled with certifications that demonstrate expertise.

Educational Requirements:

• A Bachelor’s degree in physics, computer science, electrical engineering, mathematics, or related fields is foundational.

• Advanced degrees such as a Master’s or PhD specializing in quantum computing, artificial intelligence, or quantum information science will be highly valued, particularly for research-oriented positions.

Technical Skills:

• In-depth knowledge of quantum mechanics, quantum information theory, and quantum algorithms.

• Proficiency in classical and quantum programming languages including Python, Qiskit (IBM), Cirq (Google), PennyLane (Xanadu), or similar quantum software development kits.

• Expertise in machine learning frameworks such as TensorFlow and PyTorch, including experience in designing and training neural networks.

• Understanding of hybrid quantum-classical computing architectures.

• Familiarity with cloud-based quantum computing platforms like IBM Quantum Experience, Amazon Braket, or Microsoft Azure Quantum.

Certifications and Continuous Learning:

• Earning certifications from recognized quantum computing courses and workshops (e.g., IBM’s Quantum Developer Certification) will strengthen credentials.

• Regularly updating knowledge through academic journals (like arXiv), conferences (NeurIPS, QIP), and participation in hackathons or research collaborations.

3. Personal Traits Required for Success in Quantum AI Careers

Beyond technical expertise, personal attributes play a crucial role in thriving in the cutting-edge field of Quantum AI.

• Analytical Thinking & Problem Solving: Ability to dissect complex scientific problems, develop innovative algorithms, and troubleshoot quantum systems.

• Curiosity & Passion for Learning: A strong intrinsic motivation to explore the rapidly evolving intersection of quantum physics and AI, often venturing into uncharted scientific territories.

• Adaptability & Flexibility: Openness to change and readiness to learn new methods and technologies as quantum hardware and software evolve.

• Persistence & Resilience: Patience and determination to overcome technical challenges inherent in early-stage quantum computing research and development.

• Collaborative Communication: Skill in articulating complex ideas clearly and working effectively in multidisciplinary teams that may include physicists, computer scientists, and engineers.

• Creativity & Innovation: Capacity to think outside the box, proposing novel approaches to leverage quantum advantages for AI problems.

Imagine the future leaders who will change the world with breakthrough technologies — like pioneers of artificial intelligence and quantum computing. In today’s rapidly evolving tech landscape, mastering quantum computing and artificial intelligence (AI) is becoming a fundamental skill for solving some of the world’s hardest problems. Because of this, I want to become a Quantum AI Engineer — someone who deeply understands both quantum physics and AI, and uses that knowledge to build revolutionary technologies.

Body

Step 1: High School

The first step is to study hard in mathematics and physics, especially focusing on calculus, linear algebra, probability, and quantum physics basics. To strengthen my computer science skills, I will learn programming languages like Python and practice algorithms through platforms such as Baekjoon, Codeforces, and AtCoder. Participating in competitions like KOI and IOI will sharpen my problem-solving skills and prepare me for advanced study.

Joining a science or computer science club will help me explore topics in AI and quantum computing and collaborate with others. I will also aim to prepare for admission into top universities that offer strong programs in these areas, such as POSTECH, KAIST, Caltech, and Stanford.

Step 2: Bachelor’s & Master’s Degree

During my undergraduate studies, I will complete courses in quantum mechanics, computer science, machine learning, and mathematics. I will actively participate in programming and algorithm competitions like UCPC and online challenges to enhance my coding and analytical skills.

I plan to focus on interdisciplinary research combining quantum computing and AI, working on projects involving quantum algorithms, quantum machine learning, or hybrid quantum-classical systems. Writing research papers and developing projects such as quantum AI models or software will build my portfolio and deepen my expertise.

Step 3: PhD and Beyond

In graduate school, I will specialize in quantum machine learning or quantum information science, producing numerous research papers to contribute to the scientific community. I will work closely with professors and labs at top institutions, attend conferences, and collaborate internationally.

After earning my PhD, I will pursue a career as a Quantum AI Engineer, designing innovative quantum algorithms and AI solutions that push the boundaries of computing. My work will contribute to advances in fields such as healthcare, finance, cryptography, and autonomous systems.

Conclusion

I want to become a Quantum AI Engineer because this field represents the future of technology and innovation. To achieve this, I am dedicated to learning the core principles of quantum computing and artificial intelligence through a carefully planned path — from high school studies to advanced research. With this roadmap, I will build the knowledge and skills necessary to shape the future with quantum AI.

I like solving problems. I enjoy math and programming. I also like thinking step by step and finding smart solutions. One day, I learned about a job called a quant. A quant is a person who works in finance. They use math, coding, and data to make good decisions with money. For example, they create computer programs that trade stocks or help companies understand risk. I think this job is perfect for me because it uses the skills I like. I want to become a quant, and I made a 10-year plan to follow my goal.

Body

1. High School (Now – Age 18)

Right now, I am working hard to build strong basic skills. I study math, such as calculus, statistics, and probability. I also study linear algebra using online lessons. These subjects are important for quants. At the same time, I am learning Python, a popular coding language in finance. I use Python tools like NumPy and pandas to practice. I want to take part in math and coding contests. These help me learn under pressure and think clearly. I am also reading books and watching videos to understand how finance works. This is the stage where I learn the basics and grow my interest.

2. University (Age 18–22)

In university, I will choose a major related to my goal. I might study mathematics, computer science, or financial engineering. I plan to apply to top schools in Korea like KAIST, POSTECH, or SNU. I may also look at schools in other countries if I get the chance. At university, I will take harder courses in math and programming. I will also begin learning more about real finance. For example, I want to study how the stock market works, how to price options, and how to manage risk.

I will try to get internships in banks or finance companies. These internships will give me experience and help me see how math is used in real life. I will also work on small personal projects. One idea is to build a simple trading model using data and Python. These projects will show what I can do and help me build a strong portfolio.

3. Graduate School or Job (Age 22–25+)

After university, I will decide between graduate school or a job. If I feel ready, I will apply to jobs at global companies like Citadel, Jane Street, or Korean firms. If I want to study more, I will apply for a master’s program in quantitative finance, data science, or applied math. During this time, I want to improve my skills even more. I will learn other coding languages like C++, which is also used by quants. I will practice writing reports and explaining my ideas clearly. I know that being a good quant means not only solving problems, but also working with others and sharing ideas well.

By the end of this stage, I hope to be working as a quant. I want to join a team where I can build trading models or analyze risk using data. I want to use what I learned to solve real problems.

Conclusion

Becoming a quant is not easy. It takes many years of study and practice. That is why I made this 10-year plan. I want to use this plan to guide each step of my journey. From high school to college, and from internships to my first job, I will keep learning and growing. I will build strong skills in math, programming, and finance. I will also work on projects and gain real-world experience. I believe that if I stay focused and keep working hard, I can turn my dream into reality. I am excited for the future and ready to begin this journey.

I am passionate about physics, especially quantum mechanics, and I want to use this interest in real-world technology.

Quantum computers will play a key role in the future by solving problems that classical computers cannot, such as drug discovery, cryptography, and climate simulation.

Main Body – What I will do to achieve this goal

Study physics and electronics in depth at high school, then enter KAIST and major in Physics or Electrical Engineering.

Learn programming languages like Python and tools such as Qiskit to understand and simulate quantum algorithms.

Participate in research projects, science camps, and university labs to gain experience with quantum hardware and circuits.

Conclusion

Quantum computers will change the world, and I want to be part of that future.

By combining my love for physics with hands-on learning and research, I will work toward becoming a quantum computer hardware engineer by 2035.

“Have you ever imagined a CEO who designs eco-friendly materials, manages global teams, and leads innovation from the lab to the market? That’s me in 2035.”
Future Career Introduction: I will become the CEO of a startup that develops eco-friendly materials, using chemical technology to help solve environmental problems.
Why this job matters: In an era of environmental crises and energy transition, CEOs who understand and lead technology are becoming increasingly important.
Future Outlook: The proportion of tech CEOs with STEM backgrounds is growing, especially in industries related to sustainability, chemistry, and advanced materials.

2. Body (1.5–2 minutes)

Step 1: Education and Major

• Major in Chemical Engineering, Minor in Business Administration

• Take courses in environmental chemistry, materials science, and business development

• Acquire global communication skills by learning a second foreign language such as Chinese or Spanish

Step 2: Experience and Skills

• Participate in university research projects (e.g., development of eco-friendly plastics)

• Gain hands-on experience through internships at companies like LG Chem and Hanwha Solutions

• Join startup clubs and business competitions to gain experience in business modeling

• Train in production processes, business analysis, and team leadership

Step 3: Leadership and Networking

• Join a mentoring program and connect with current CEOs and CTOs

• Practice TED-style presentations to improve public speaking and communication skills

• Pitch early startup ideas to accelerators and validate business feasibility

3. Conclusion (20–30 seconds)

“By combining science with leadership, and engineering with business, I’ll lead a company that changes the world – not just with ideas, but with real products that solve real problems.”
Core Summary: My plan is to build a strong technical foundation through a chemical engineering major, while gaining business experience and leadership skills to realize my dream of becoming a CEO.

Hello everyone,

I’ve always been interested in science and technology. Recently, I learned about a career called a Weapons System Developer. This job involves designing and improving advanced weapons like smart bombs and unmanned drones. These technologies help protect our country and keep people safe. I think this job fits me well because it combines my passion for chemistry and engineering. So, I made a plan to become a weapons system developer by 2035.

Body

High School (Now – Age 18)

Right now, I’m focusing on building a strong foundation in science and math. I study subjects like chemistry and physics, which are important for understanding explosives and engineering principles. I’m also learning programming to handle simulations and data analysis. In addition, I want to join science clubs and participate in competitions related to engineering and technology. This will help me develop practical skills and teamwork experience.

University (Age 18–22)

In university, I plan to major in Chemical Engineering at a top school like POSTECH or KAIST. I will study key subjects such as thermodynamics and explosives chemistry, which are essential for developing weapon systems. I also want to gain hands-on experience through internships at companies like Hanwha Aerospace or research institutes like ADD (Agency for Defense Development).

I will try to get certifications like Chemical Process Engineer and Hazardous Materials Safety Officer to improve my qualifications. Besides academics, I will attend defense technology conferences and connect with mentors to learn more about the field.

Graduate School or Job (Age 22–25+)

After university, I will decide whether to pursue graduate studies or start working. If I continue school, I might study further in defense technology or chemical engineering. If I enter the workforce, I hope to join ADD or a defense company where I can work on smart weapons and drone projects.

During this stage, I will improve my technical skills and collaborate with experts. I will also focus on staying updated on new defense technologies and maintaining a strong work ethic.

Conclusion

Becoming a weapons system developer requires dedication and continuous learning. That’s why I made this plan — to guide me step by step from high school to my future career. I will keep strengthening my knowledge in chemistry, engineering, and programming, while gaining practical experience. I believe that with hard work and passion, I can contribute to protecting my country through advanced technology. I’m excited to start this journey and look forward to the future.

Thank you for listening.

Hello everyone.

Do you remember the Korea Materials Congress, GCIM 2025?

I had a chance to attend it, and I was really impressed by the development of advanced new materials — especially those used in semiconductors. It made me want to research these materials, which are used in things like smartphones.

That experience is what made me interested in the job of a semiconductor materials scientist. I think it is exciting to discover new materials and contribute to innovation in semiconductor technology.

[Body]

As you can see in my poster, this job includes many different tasks.

A semiconductor materials scientist studies and develops new materials with unique electrical, thermal, and mechanical properties. They also improve manufacturing processes, analyze materials using advanced tools, and evaluate how well devices perform.

Other important parts of the job include working with engineers, solving problems during production, and keeping up with the latest research.

To prepare for this job, I need a strong background in solid-state physics, materials science, and semiconductor device physics.

I also need skills in data analysis, computational modeling, and programming.

The journey to become a semiconductor materials scientist starts in high school — by focusing on math and science, and joining STEM-related activities.

Next, I plan to major in materials science or a related field in college, and continue my studies in graduate school to learn more deeply.

Getting hands-on experience through internships at semiconductor companies is also important before starting a full-time job in the field.

According to recent data, the global semiconductor materials market is expected to grow from 62.4 billion dollars in 2023 to about 96.8 billion dollars in 2033.

As AI, electric vehicles, and 5G technology grow, the need for new materials increases — which means this field has a lot of potential.

[Conclusion]

One scientist I really admire is John Bardeen, who is also on my poster.

He invented the transistor in 1947 and co-developed the BCS theory of superconductivity, which made a huge impact in both technology and physics.

Just like him, I want to become a scientist who leads innovation in semiconductors.

My ultimate dream is to work at the Samsung R&D Center, and help create the next generation of materials that move the world forward.

Thank you for listening!

Have you ever wondered what powers your smartphone, electric cars, or even space rockets?

The answer lies in semiconductors—the tiny electronic components that drive all modern technologies.

As artificial intelligence continues to evolve rapidly, the need for smaller, faster, and more energy-efficient chips becomes even more urgent.
And at the core of those technologies are the semiconductor device physicists—the people who design and understand how electrons move through these devices.

By 2035, I see myself as one of them:
a semiconductor device physicist, working at the frontiers of nanotechnology and quantum-scale electronics.

This job is not only highly technical, but increasingly essential.
According to OECD reports, the global semiconductor market is expected to double by 2035, reaching over 1.3 trillion US dollars.
The demand for advanced chips will only grow with the rise of AI, electric vehicles, and quantum computing.

But my interest goes deeper than just market trends.
I'm fascinated by how invisible particles like electrons can shape the visible world.
I want to become someone who not only understands this invisible world—but also uses physics to build the future.

[Body]

1. Education Path

To achieve my goal, I will first major in Physics at KAIST, starting in 2027.
I plan to focus on electromagnetism, quantum mechanics, and solid-state physics, which are essential for understanding how semiconductor devices work.

In high school, I’ve already been deeply engaged in physics—studying semiconductor theory, electric fields, and signal conduction, while also conducting experiments that connect theory with practice.

2. Experience and Skills

Recently, I was selected for a pre-URP program at KAIST, where I’m currently studying the topic: “Fabrication and Electrical Characterization of Thin-Film Transistors Based on 2D Semiconductors.”

This hands-on research gives me direct experience with cutting-edge device fabrication and material analysis, and is helping me build practical skills in a field I’m truly passionate about.

In the future, I plan to intern at research institutions such as KIST or Samsung Advanced Institute of Technology, where I can work on real-world challenges in semiconductor material development and device design.

3. Networking & Mindset

Success in this field requires more than technical knowledge—it demands curiosity, perseverance, and guidance.

I will actively seek mentorship from professors and researchers, participate in global conferences like IEDM (International Electron Devices Meeting), and stay updated with the latest trends in nanoelectronics.

Even when faced with complex challenges—like the abstract theories of quantum mechanics or the precision of nanodevice fabrication—I’ll stay motivated by asking questions and exploring until I find answers.

[Conclusion]

In 2035, I envision myself as a semiconductor device physicist, leading breakthroughs in how we process and store information.

To reach that goal, I’ll continue building a strong foundation in physics, gain real-world research experience—like my current project on 2D semiconductor-based thin-film transistors at KAIST—and grow through mentorship and global collaboration.

I’m not just preparing to join the tech industry—I’m preparing to shape the next generation of technology.

[Summary]

-Goal: Semiconductor Device Physicist (2035)
Why: Key to future tech (AI, quantum, EVs)
-Education: B.S. in Physics @ KAIST → Ph.D. in Applied Physics
-Experience:
• KAIST pre-URP – 2D Semiconductor TFT Fabrication & Electrical Analysis
• Future internships at KIST/Samsung, experimental physics projects

-Mindset: Curiosity, mentorship, global scientific engagement

A chemistry professor teaches university students about the principles of chemistry, including organic, inorganic, physical, and analytical chemistry. They also conduct scientific research, publish academic papers, and guide graduate students in their thesis or laboratory work. In addition to teaching, professors often contribute to the scientific community through conferences, peer reviews, and collaborations with industries or research institutions.

2. Job Outlook

   The job outlook for chemistry professors is positive, especially with the global emphasis on STEM education and scientific innovation. According to the U.S. Bureau of Labor Statistics (2024), employment for postsecondary teachers—including chemistry professors—is projected to grow 8% from 2022 to 2032, which is faster than the average for all occupations. Professors with strong research portfolios and interdisciplinary knowledge are expected to be in higher demand.

3. Path to Becoming a Chemistry Professor

   • Earn a Bachelor's Degree
     Becoming a chemistry professor begins with earning a bachelor’s degree in chemistry or a related field, which usually takes about four years. During this time, students study fundamental chemistry, mathematics, and physics.

     
     

   • (Optional) Complete a Master's Degree
     Some students choose to continue with a master’s degree in chemistry, which takes around two additional years. Although not always required, this step helps deepen research experience and build a specialization.

     
     

   • Earn a Ph.D. in Chemistry
     The most important step is earning a Ph.D. in chemistry, which takes about four to six years. Ph.D. candidates conduct original research, publish scientific papers, and often work as teaching assistants.

     
     

   • Gain Postdoctoral Research Experience
     After completing the doctorate, many aspiring professors pursue postdoctoral research for one to three years. This phase helps them strengthen their research portfolio, develop professional networks, and improve their chances of getting a faculty position.

4. Skills and Competencies Needed

   1. Subject Expertise
   A professor must have a deep and broad understanding of various chemistry disciplines, including organic, inorganic, physical, and analytical chemistry.

   2. Strong Research Skills
   This includes the ability to design experiments, analyze data, and publish findings in reputable scientific journals.

   3. Communication Skills
   Professors need to explain complex concepts clearly during lectures and also present their work effectively at academic conferences.

   4. Critical Thinking
   They must be able to approach scientific problems logically, test hypotheses, and draw evidence-based conclusions.

   5. Academic Writing Skills
   Writing research papers, grant proposals, and reports—often in English—requires precision, clarity, and persuasiveness.

   6. Collaboration and Leadership
   Professors supervise research teams, mentor students, and work with colleagues from various disciplines. Leadership in lab management is also important.