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join our research group to develop advanced techniques for ultra-high field (UHF) perfusion imaging. The successful candidate will have an opportunity to work with a highly experienced and multi
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, brain imaging, and psychopathology research. This position will include a central role in an active, funded collaboration between the Elliott Lab and researchers at Harvard University, Stanford University
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model development. -Proficiency in molecular and cellular biology techniques (e.g., DNA/RNA extraction, flow cytometry, histology, fluorescence imaging). -Proven record of first-author publications in
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indicators (GEVIs) for single-neuron, single-spike resolution recordings in behaving animals. The incoming candidate in the Kannan lab will apply advanced optical tools and multipopulation voltage imaging
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in R, MATLAB, Python and/or other programming languages. Experience in AI and machine learning techniques applies to physiological, neural, and imaging data. Preferred qualifications Experience with
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related field, and experience in one or more of the following areas: multiphoton imaging, optogenetics, calcium imaging, and / or in vivo electrophysiology. Applicants without prior experience in
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/molecular approaches, in vivo imaging, behavior, histology, and EEG. The desire to learn new techniques and work as part of a collaborative team is strongly encouraged. Training in new techniques would be
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professional domains and a desire to ask big-picture questions. Preferred Qualifications: Familiarity with natural language processing (NLP) or network science. Experience with machine learning libraries like
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. This position offers the opportunity to work in a vibrant, well-funded lab with strong collaborations across neuropathology, neurology, and neuroscience, and access to advanced resources such as imaging cores
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prototype device into a minimum-viable-product that can be utilized in hospitals and clinics. The postdoc will assist the laboratory in equipping the current prototype device with new features and