Positions

 

 

 

Functional Neuroimaging Clinical Research Fellowship
The ideal candidate would have a M.D. or M.D./Ph.D. with clinical training in neurology, neurosurgery, or neuroradiology. Ideally, they would also have strong computer and engineering skills, and experience with functional MRI (fMRI), PET, magnetoencephalography and/or electroencepholography (MEG/EEG). The fellow would interpret advanced functional neuroimaging studys, attend meetings relating to presurgical mapping, and undertake independent research. The candidate will interact with world-class engineers, physicists, and physicians at the MGH-Martinos Center, Harvard Medical School, and Massachusetts Institute of Technology to advance medical science. Training would include research integrating and evaluating high-field MRI, MR-PET, and MEG/EEG in epilepsy and other subjects.

REQUIREMENTS: M.D. with a residency in radiology, neurology, or neurosurgery. Additional degree in Biomedical Engineering, Computer Science, Physics, Cognitive Neuroscience is helpful, but not required. Candidates must be able to work independently. Programming experience is desired. Good organizational skills is a must.

The Massachusetts General Hospital is an equal opportunity and affirmative action employer.

CONTACT: Please email Dr. Steven Stufflebeam with a cover letter and CV to sms at nmr.mgh.harvard.edu. Two letters of recommendation will be required. If you have any questions please email Dr. Stufflebeam or call (617) 726-0963.

Post-Doctoral Fellowship

Research Assistant Position

The Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital and Harvard Medical School has an immediate opening for a postdoctoral fellow and research assistant in the area of software development for non-invasive neuroscience analysis.

 

This fellowship is funded by and part of the TRANSFORM DBS project, a Federally funded initiative to revolutionize psychiatric treatment through large-scale human neuroscience and the development of new devices for electrical brain stimulation. The fellow will have an opportunity to work directly with leaders in psychiatry, neurosurgery, neurology, and brain imaging. We anticipate substantial opportunities for mentoring, collaboration development, and high-visibility publication. The project is part of President Obama’s BRAIN Initiative, and both data and software will be widely disseminated. Previous projects in the Martinos Center, including Freesurfer and MNE, have gained widespread adoption as standards in the neuroscience community.

 

As part of TRANSFORM, a team of investigators will be gathering non-invasive (fMRI, MEG, and EEG) and invasive (ECOG, LFP, single unit) data from awake behaving humans across a variety of neurological and psychiatric conditions. These data will feed computational modeling that intends to capture aspects of the brain at sub-cellular to hemispheric scales, which in turn will inform the development of neurostimulators that sense and modify the brain’s electrical activity. To achieve this aim, data from these multiple modalities must be fused into a unified representation for combined analysis, visualization, and dissemination. This involves multiple challenges, including inverse (source localization) techniques for deep/subcortical sources, representation of both volume and surface-patch sources in the same visualization/analysis tools, and accurate visualization of data acquired in the same brain but at multiple points in time/space. In later years, the project scope of work will expand to expand considerations in signal processing and noise mitigation, with the aim of creating turn-key solutions to take data directly from scanners into cleaned and visualizable representations.

 

The fellow will address these challenges by developing extensions to the MNE and Freesurfer packages under the direction of Drs. Steven Stufflebeam and Matti Hamalainen. The initial focus will be on co-registration and co-visualization of fMRI with MEG/EEG and invasive with non-invasive data. Subsequent work, selected partially under the fellow’s discretion, will involve further topics in signal processing and source localization. This is a rich area with many unresolved questions, and we anticipate that the incumbent will be able to establish a foothold in an area for future independent investigation post-fellowship. Through the collaboration, substantial mathematical and statistical methods consulting will be available to assist with this.

 

Requirements for the post-doc position include:

• Completion of a PhD or equivalent degree; candidates who are just finishing doctoral study must provide strong assurance of completion of all requirements at least two months in advance of proposed start date. A PhD in a field related to medical imaging and medical physics is preferred, but applications are welcomed from fields such as mathematics, computer science, neuroscience, or statistics if the candidate can demonstrate a grounding in brain imaging.
• Extremely strong programming skills, with evidence of formal training or prior experience in designing for large-scale use and reuse. Prior knowledge of Python and MATLAB are essential; C is strongly desirable.
• Understanding of the physical and mathematical underpinnings of MEG/EEG data and the basics of their analysis. Formal research in this area is not required if evidence of knowledge can be demonstrated.
• Strong communication skills on technical topics. English fluency, both written and spoken, is required; incumbents will be expected to present data and approaches to a broad technical audience, including non-mathematicians and non-neuroscientists.
• Demonstrated capability for independent work and creative problem-solving. Reference letters, if provided, should give specific examples of the candidate’s accomplishments in these areas.
• Organizational and collaborative skills, particularly the ability to work in an environment with colleagues who are highly diverse in technical background, level of training, and interaction styles.
• Familiarity with scientific and technical dissemination, as evidenced by a good publication record in well-read journals and well-attended conferences.

Requirements for the research assistant position include:

 

• Completion of a B.S./B.A. or equivalent degree in engineering, physics, cognitive neuroscience or related field.
• Extremely strong programming skills, with evidence of formal training or prior experience in designing for large-scale use and reuse. Prior knowledge of Python and MATLAB are important; C is strongly desirable.
• Strong communication skills on technical topics. English fluency, both written and spoken, is required; incumbents will be expected to present data and approaches to a broad technical audience, including non-mathematicians and non-neuroscientists.
• Demonstrated capability for independent work and creative problem-solving.
• Organizational and collaborative skills, particularly the ability to work in an environment with colleagues who are highly diverse in technical background, level of training, and interaction styles.

 

Preference will be given to candidates who can demonstrate at least one of:

• Prior experience with or contribution to open-source software projects, particularly in the scientific software domain.
• Work in large and/or distributed teams during prior projects. Collaborative or interdisciplinary activities are especially valued.
• Prior leadership activities, such as service in leadership roles in postdoctoral or graduate organizations.
• Flexibility and adaptability, often demonstrated by prior work or training across disparate disciplines.
• Past work with computational simulation or modeling of the brain.
• Past empirical neuroscience work, including both data collection and analysis. Human subjects experience is not at all required, but will be favored.

Duration: The successful candidate will be expected to commit to a position of at least two years. We are willing to extend up to four years, contingent on good performance, cultural fit, and availability of ongoing funding.

Start date: Earliest possible

Contact: Prof. Steven Stufflebeam

 

To apply, please send a cover letter highlighting particularly relevant qualifications, a complete CV with list of publications, as well as the contacts of at least two references (including your PhD supervisor).

 

Massachusetts General Hospital is an equal opportunity employer. We welcome and encourage candidates of every national origin, ethnicity, sexual/gender orientation, and disability to apply if they are able to fulfill the position requirements. Candidates need not be US citizens or permanent residents.

Research Assistant

A full-time Research Assistant (RA) position is available at the Martinos Center for Biomedical Imaging. Applicants must have excellent computer skills. They would be involved in acquiring and analyzing functional MRI (fMRI) combined with magnetoencephalography (MEG) and electroencepholography (EEG), and comparing the results with intracranial neurophysiology measurements. This would be an excellent position for someone interested in a 1-2 year position prior to applicaiton to graduate school or medical school.

REQUIREMENTS: Undergraduate or graduate degree in Biomedical Engineering, Computer Science, or Physics. Cognitive Neuroscience or related field is possible for candidates who have excellent quantitative and computer skills. Candidates must be able to work independently. Experience with MATLAB and Unix is a must.  If you have any questions please email Dr. Stufflebeam or call (617) 726-0963.

To apply, email CV, description of research experience, and statement of goals and interests to: Steven Stufflebeam sms at nmr.mgh.harvard.edu.

HST M.D. Student Research Assistant

A Research Assistant (RA) for an HST M.D. student is available at the Martinos Center for Biomedical Imaging. Applicants must have excellent computer skills. The student would attend meetings relating to presurgical evaluation of epilepsy, and brain tumor patients.  The position duties include call patients for research studies involving functional imaging.  They would also be involved in acquiring and analyzing functional MRI (fMRI) combined with magnetoencephalography (MEG) and electroencepholography (EEG), and comparing the results with intracranial neurophysiology measurements. The project would make an excellent M.D. thesis.

REQUIREMENTS: Must be an HST student in the M.D. or M.D./Ph.D. programs. Undergraduate or graduate degree in Biomedical Engineering, Computer Science, Physics, Cognitive Neuroscience or related field. Candidates must be able to work independently. Experience with MATLAB and Unix is suggested, but not a requirement.  If you have any questions please email Dr. Stufflebeam or call (617) 726-0963.

To apply, email CV, description of research experience, and statement of goals and interests to: Steven Stufflebeam sms at nmr.mgh.harvard.edu.