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of developmental and/or regenerative neurobiology, neuronal cell biology, and/or nervous system disease involving the cerebral cortex to join an ongoing research program focusing on the developmental, degenerative
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be
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for analysis (e.g., text manipulation); One or more computational environments for statistical analysis (e.g., MATLAB, Stata, R, or Python); Creating and managing very large datasets; Managing and mentoring
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contribute to technical deliverables and help to plan for technology translation. Basic Qualifications PhD in engineering, biomechanics, or a related field. Additional Qualifications Interest in
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, scientists, clinicians and artists that work at the intersection of art, cell biology, design, materials science, and computational modeling. Insta: Studio_DBG YouTube: Disease Biophysics Group Website
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especially encourage candidates with proven experience in applying computational and experimental methods to social scientific questions – including aptitude in working with large-scale datasets and text
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interpersonal and communication skills. While not a must, a strong background in computational methods and/or statistical methods is a plus. Special Instructions Applicants should submit a formal application and
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complex behaviors in rats using techniques drawn from circuit-driven neuroscience, and computational ethology. The opening is for a postdoctoral fellow with expertise in systems neuroscience, including some
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Bioinformatics, Computational Biology, or related areas; Hands-on experience with, or a strong interest in, bioinformatics programming, including Linux, scripting, and R; Expertise in data mining and cleaning
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of Organismic and Evolutionary Biology, which is a vibrant community of cross-disciplinary biological scientists at Harvard University. Basic Qualifications A Ph.D. degree in Bioinformatics, Computational Biology