Postdoctoral research fellow at Harvard Medical School & Massachusetts General Hospital – Machine learning for imaging the wiring of the brain across scales
We are seeking talented and driven postdoctoral fellows with experience in ML for image analysis to join the computational team of the center for Large-Scale Imaging of Neural Circuits (LINC). The LINC project brings together a multi-disciplinary group of experts from 8 institutions (Brigham and Women’s Hospital, Columbia University, Harvard University, Massachusetts General Hospital, Massachusetts Institute of Technology, University College London, University of Rochester, Weill Cornell Medicine) to develop novel technologies for imaging brain connections down to the microscopic scale. The computational team will develop tools for analyzing the data generated by the microscopy and MRI teams, and reconstruct axonal projections that will be used by the circuits team to study brain circuits relevant to neuromodulation for motor and psychiatric disorders. The project is one of the 5 comprehensive centers funded by the BRAIN Initiative CONNECTS network.
The postdoctoral fellows will be situated at the Athinoula A. Martinos Center for Biomedical Imaging. The position offers the opportunity to work closely with the Martinos Center’s leading experts in image acquisition, analysis, and clinical applications, and to join the vibrant neuroimaging community of Boston.
Potential projects fall in three areas:
- Analysis of microscopy data: Algorithms for high-throughput, automated analysis of optical and X-ray microscopy datasets, including cross-modal registration and axon segmentation.
- Inference of fiber architectures from diffusion MRI: Development of models that can be trained on ground-truth microscopy and diffusion MRI data to infer fiber architectures directly from diffusion MRI.
- Multi-scale tractography: Algorithms that can take advantage of data across any combination of modalities and scales to improve reconstruction of connectional anatomy, ex vivo or in vivo.
Strong programming skills, and a Ph.D. in electrical engineering, biomedical engineering, computer science, applied math, or related field are required. Candidates with a strong background in any aspect of computer vision/machine learning are encouraged to apply. Experience working with microscopy or diffusion MRI data is an asset but not required. Creativity, initiative, proven ability to publish, and excellent oral and written communication skills are key.
The positions are full-time with benefits and available immediately. The search will continue until the positions are filled. Salary will be based on qualifications and experience. The Massachusetts General Hospital is an Equal Opportunity/Affirmative Action Employer.
Applicants should submit a curriculum vitae, the contact information of two references, and a cover letter describing their research background, interests, and professional goals by email to Dr. Anastasia Yendiki (ayendiki [at] mgh.harvard.edu).