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-polysaccharide assemblies to naturally occurring and engineered polymers and industrially relevant catalytic materials. The Opportunity The successful candidate will lead an interdisciplinary research program in
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help shape a major research direction at the intersection of AI, neuroscience, and human health. Required Qualifications: A Ph.D. in computer science, computational neuroscience, biomedical engineering
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, develop independent lines of inquiry, present at national and international conferences, and collaborate with a multidisciplinary network of investigators. The position provides strong mentorship and career
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transdisciplinary network. Required Qualifications: A completed Ph.D. in a relevant field, such as the social sciences, environmental studies, sustainability science, science and technology studies, public policy
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interdisciplinary. Group members come from backgrounds including microbiology, chemistry, chemical biology, biochemistry, physical chemistry, biophysics, and engineering, and we value the different experimental and
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networks and will have access to the computational and informatics infrastructure required for clinical AI research. The position offers opportunities to work at the intersection of methodological
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include: Identifying spatial determinants of therapeutic delivery and response in solid tumors, including antibodies, antibody-drug conjugates, immunotherapies, targeted therapies, and engineered cell
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for action ("affordances") shape neural representations, perception, and behavior. Why this position? You will sit at the center of a uniquely cross‑disciplinary team and work closely a network of
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. The fellow will also work closely with SCEC Senior Machine Learning Engineer Dr. Lauren Klein Dubin, who will provide day-to-day supervision of the fellow's technical work. The fellow will have opportunities