dieter.meyerhoff@ucsf.edu                          David.Pennington2@va.gov

415-221-4810 x24803                                    415-221-4810 x24504 at the SF VA

 Apply for this position online at: https://www.med.upenn.edu/apps/faculty_ad/index.php/g/d4511

 

The postdoc will work on an R01-funded project that aims to map human white-­matter anatomy using ex vivo diffusion-weighted MRI and optical coherence tomography at microscopic resolutions; and to use this mapping to inform algorithms for analyzing in vivo diffusion-weighted MRI data. Involvement is also possible in other ongoing projects, including in vivo MRI studies of white-matter connections in psychiatric disease, and ex vivo validation of diffusion-weighted MRI with chemical tracing. For more information on research projects, see: http://scholar.harvard.edu/a-y

 

The position is within the Laboratory of Computational Neuroimaging, offering exposure to research on a wide range of MRI data analysis and acquisition methods, as well as opportunities to teach in courses and training workshops. 

 

The ideal candidate has a Ph.D. in electrical engineering, biomedical engineering, computer science, or related field. Prior research experience with diffusion-weighted MRI data analysis or acquisition is preferred. Creativity, initiative, proven ability to publish, and excellent oral and written communication skills are key.

 

Applicants should submit a curriculum vitae, the contact information of least two references, and a cover letter describing their research background, interests, and professional goals by email to Dr. Anastasia Yendiki (ayendiki@mgh.harvard.edu).

 

The postdoctoral fellow will be responsible for overseeing all aspects of the neuroimaging component of this project. Collecting high quality MRI data and then apply advanced data analytic approaches (graph theoretical network analysis, machine learning, multivariate modeling). 

 

Necessary qualifications include: 1) a PhD in neuroscience, psychology, cognitive science, computer science or a related field; 2) experience with collecting, processing and analyzing functional and structural MRI data; 3) experience with typical neuroimaging software packages - fMRI/MRI/DTI (e.g., FSL, AFNI, SPM, Freesurfer); 4) experience implementing quality coding, particularly with python, unix and/or matlab; and 5) meticulous attention to detail. 

 

Preference will be given to candidates who additionally have: 1) experience working with individuals with mood disorders; and/or 2) have previous experience with advanced analytic techniques (e.g., multivariate approaches, machine learning, and/or graph theory).

 

Interested persons may send their CV and a cover letter to David Schnyer – schnyer@utexas.edu. Here at OHBM Vancouver if you want to meet and chat!

 

The postdoctoral fellow will lead neuroimaging projects involving multimodal MRI (functional, diffusion) and NIRS imaging to understand the effect of cognitive and neurofeedback training on brain networks in children and older adults. The postdoctoral fellow will participate in collecting and analyzing multimodal neuroimaging data, training and supervising students and research assistants, preparing manuscripts for publication, as well as assisting with grant applications. The position provides a unique training opportunity in advanced neuroimaging, graph theoretical and connectomics methods, and neurocognitive intervention.

 

Requirements: 

-       PhD (or MD) or equivalent in neuroscience, computer science, psychology, statistics, engineering or a related field.    

-       Familiarity with neuroimaging data collection and related analysis packages

-       Experience with programming in Matlab, python and/or other related computing languages.

-       Strong writing skills demonstrated by peer reviewed publications 

-       Strong interpersonal, organizational and mentoring skills

-       Familiarity with advanced data analysis methods, multivariate statistics, machine learning, data mining and visualization, and cloud computing is a plus. 

 

The research in Dr. Hosseini’ group crosses multiple disciplines including computational neuropsychiatry, cognitive neuroscience, multimodal neuroimaging and neurocognitive rehabilitation. The computational neuropsychiatry research mainly involves investigating alterations in the organization of connectome in health and disease (ADHD, Alzheimer’s, Stroke, etc.) using state of the art neuroimaging techniques (fMRI, sMRI, DWI, functional NIRS) combined with novel computational methods (graph theoretical and multivariate pattern analyses). The ultimate goal is to translate the findings from computational neuropsychiatry research toward developing personalized interventions. Dr. Hosseini’s group have been developing personalized interventions that integrate computerized cognitive rehabilitation, real-time functional brain imaging and neurofeedback, as well as virtual reality (VR) tailored toward targeted rehabilitation of the affected brain networks in patients with neurocognitive disorders.

The position involves leading/assisting with various aspects of multimodal neuroimaging studies in human including assessments, neuroimaging data collection, preprocessing and analysis as well as taking part in manuscript preparation. The focus of the computational neuroimaging studies is on investigating alterations in the organization of human connectome in health and disease (Alzheimer’s, ADHD, Stroke, etc.) using state of the art neuroimaging techniques (fMRI, sMRI, DWI, fNIRS) combined with novel computational methods (graph theoretical and multivariate pattern analyses). The translational projects involve developing personalized interventions that integrate computerized cognitive rehabilitation, real-time functional brain imaging and neurofeedback, as well as virtual reality (VR) tailored toward targeted rehabilitation of the affected brain networks in patients with neurocognitive disorders. 

Requirements: 

-  Bachelors in Neuroscience, Psychology, Computer Science, Statistics, Physics or a related field. 

-  Experience with programming in Matlab, Python, and/or other related computing languages. 

-  Strong analytical skills. 

-  Strong interpersonal and organizational skills. 

Preferred Qualifications: 

-  Familiarity with neuroimaging (fMRI, fNIRS) data collection and related analysis packages (SPM, FSL, AFNI, HOMER, etc.). 

-  Strong written communication skills. 

-  Previous experience with human subject (behavioral/neuroimaging) research.

To apply: Applicants are invited to send their resume and a cover letter (optional) to study_brain@stanford.edu. 

A Postdoctoral Position in the area of Neural Engineering is available in the lab of Jacek Dmochowski at the City College of New York (CCNY).  Research in the lab is directed towards the development of non-invasive techniques for stimulating the human brain and decoding its activity.  For this we employ a variety of tools including electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and transcranial direct current stimulation (tDCS).  The Department of Biomedical Engineering at CCNY has a core strength in human neuroscience and is home to three neural engineering labs that closely collaborate.  

 

Candidates should have a Ph.D. in engineering, physics, computational neuroscience, or a closely-related field.   Experience with computer programming in Matlab or Python is strongly preferred.  The successful candidate will be given the opportunity to lead one or more projects that involve both experimental (human subjects research) and computational (machine learning, biophysical modeling) components.   The candidate will be involved in all facets of the research including experimental design, data collection, analysis, and preparation of manuscripts.    

 

The position is for two years and has a flexible start date.  Salary is competitive and based on years of experience.  Interested candidates should submit a C.V., a short statement of research experience and interests, as well as contact information for at least two references to jdmochowski@ccny.cuny.edu.  

 

For more details about the lab, please visit the website at jd-lab.org.

Applicants must have (i) a Ph.D. in a discipline associated with Science of Learning and expertise in quantitative analysis and computational skills; (ii) strong evidence of foundational research training in methods of brain imaging (e.g. high-density EEG, fNIRS, MEG, and fMRI); (iii) an innovative research program that translates (or has the potential to translate) real world educational challenges into experimentally trackable neuroscience problems and solutions; (iv) a track record of working collaboratively across disciplines; (v) strong interest in and commitment to team development and delivery of core courses in Neuroscience for Education at Undergraduate, Master’s and Ph.D. levels. Undergraduate teaching will include contributing to Common Core courses, as well as cross-Faculty programs in Neuroscience, working with the Psychology Department (Faculty of Social Sciences).

The appointee will be responsible for developing a research program in Neuroscience for Education (inclusive of combined neuroimaging and behavioral experimentation) as an integral part of the Science of Learning Strategic Research Theme; securing external competitive research grants and publications in peer reviewed journals; enhancing collaboration between the Faculty of Education and other Faculties with interests and expertise in Science of Learning research; engaging in teaching and program development, graduate student mentorship, and disseminating research findings to schools and the general public.

Information about the Faculty of Education can be obtained at http://www.hku.hk/education.  Enquiries relating to the roles and responsibilities of the position should be addressed to Professor Akaysha Tang, Faculty of Education (e-mail: actang@hku.hk).

A highly competitive salary commensurate with the appointee’s qualifications and experience will be offered, in addition to annual leave and medical benefits. The appointment will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totaling up to 15% of basic salary. Housing benefits will be provided as applicable.

Applicants should send (1) a completed application form (Form 341/1111), which can be downloaded at http://www.hku.hk/apptunit/form-ext.doc); (2) an up-to-date C.V.; (3) a cover letter discussing: (i) evidence of your qualifications, (ii) publications and other forms of research outputs, (iii) research programs you have led or participated, if any, (iv) details of how your expertise can inform life-long learning across diverse populations, or how you plan to do so in the future, (v) your teaching experiences and teaching philosophy; and (4) three representative publications to edufaca@hku.hk.

For more information about the lab, please visit http://nfe.edu.hku.hk/.

Located at the heart of the culturally diverse and vibrant city of Hong Kong, where the East meets and mixes with the West, the newly established NfE Lab is part of the Science of Learning Strategic Initiative, dedicated to both basic and translational research. By investigating learning in the natural social, emotional, and developmental context, the NfE Lab aims to uncover generalizable learning principles at multiple levels of analysis and in multiple domains of learning (e.g. math and language) and create societal impact via enhancement of learning, improvement of teaching practice, and informing educational policy making. Leveraging recent advances in neurotechnology development, the NfE Lab sets its priority on bringing laboratory-based neuroimaging research into the real world of learning.

Applicants should possess a Ph.D. degree in fields associated with Science of Learning, including but not limited to cognitive neuroscience, psychophysiology, neuroimaging, computational neuroscience, computer science, electrical and computer engineering, and physics, with at least two years of experience in either high-density EEG (post 1– Ref.: 201700564) or fNIRS (post 2 – Ref.: 201700565) research. Applicants with technical skills in both fNIRS and hdEEG are particularly welcome to apply.

The appointees are expected to have substantial experience and a publication record in interdisciplinary and collaborative neuroscience research on learning broadly defined; and demonstrated ability to design and conduct research projects and mastery of either high-density EEG or fNIRS techniques.

The duties and responsibilities of the appointees include participating in proposal writing and research designs; implementing and performing hd EEG or fNIRS experiments involving participants across a wide range of ages in the laboratory or school/home settings; analyzing data; and writing and submitting manuscripts for peer reviewed journals relevant to science of learning.

Information about the Faculty and NfE Lab can be obtained at http://www.hku.hk/education and http://nfe.edu.hku.hk. Enquiries about the post should be addressed to Professor Akaysha Tang, Director of the NfE Lab, Faculty of Education (e-mail: actang@hku.hk).

A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits.

Applicants should send a completed application form together with an up-to-date C.V. to eduface@hku.hk. Applicants should state clearly which post(s) and the reference number(s) they wish to be considered for. Application forms (341/1111) can be downloaded at http://www.hku.hk/apptunit/form-ext.doc.

For more information about the lab, please visit nfe.edu.hku.hk/.

This interdisciplinary position will involve, in collaboration with other members of the team: setting up behavioural and fMRI designs, recruiting and testing children and adolescents, analysing the data and writing results.

The cognitive neuroscience community in Marseille is very active, and takes advantage of many facilities (state-of the art EEG, MEG, a newly renovated fMRI center, NIRS) and benefit from close interactions between healthy humans, clinical and animal research.

Marseille is one of the most vibrant city in the South of France, with wonderful beaches, eating and hiking possibilities

Applications should be sent by email (marie-helene.grosbras@univ-amu.fr) and should include a CV, a brief statement of research interests, the expected date of availability and the names of 2 references. Also here at OHBM Vancouver if you want more info!

 

LMN has a vibrant research program, applying multimodal imaging in studies that use molecular (PET), functional (BOLD fMRI, perfusion MRI), and structural measures (sMRI, DTI). Postdoctoral fellows, based in LMN, will have the opportunity to interact with a well-established group of investigators within the laboratory and with other neuroimaging scientists at UCLA. 

 

The project on which the postdoc will be working will involve setting up behavioral experimental task paradigms for use in and out of the MRI setting, recruiting healthy adult participants, analyzing behavioral and MRI data, and writing manuscripts. 

 

Interested applicants should meet the following criteria:

1) Interest in social neuroscience and decision making. Experience in social neuroscience or social psychology preferred

2) Technical experience in functional MRI data acquisition and analysis. Experience in both univariate and multivariate statistical analyses is preferred.

3) Strong programming skills (e.g., Matlab, Python, and/or shell scripting)

4) Strong statistical background

5) Doctoral degree (PhD in cognitive or affective neuroscience, cognitive science, experimental psychology, or related discipline)

 

Salary will be commensurate with training level. UCLA is an equal-opportunity employer. Women and minorities are encouraged to apply.

 

Earliest start date is August 2018. 

 

APPLICATION PROCEDURE: 

Applications must include the following items in order to be considered:

1. Current curriculum vitae

2. Letter of intent

3. Names of two references

 

Interested applicants should email Dara Ghahremani (darag@ucla.edu)

More information about LMN: 
http://www.semel.ucla.edu/laboratory-molecular-neuroimaging