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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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Brain Foundation Models at Stanford University We are recruiting a highly motivated Postdoctoral Research Fellow to join an interdisciplinary effort at Stanford University focused on building next
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, Division of Neonatology and the Neonatal Engineering, Signals, and Technology (NEST) Lab are seeking a creative, motivated, and collaborative Postdoctoral Fellow to join our team and conduct research focused
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(1-2) Applicants with expertise in one or more of the following areas are encouraged to apply: * Foundation Models * Agentic AI * Reinforcement Learning * Medical Image Analysis Position 2: Intelligent
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know far less about how societies actually accomplish such changes in ways that are sustainable, lasting, and truly transformative. Through transdisciplinary approaches, TSP builds on foundational
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engineering, and advanced analytics to develop novel approaches that improve patient outcomes and expand access to life-saving surgical interventions. The fellowship includes opportunities for mentorship
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., state screener lists) and contributing to the technical foundations of the tool. ROAR is a dynamic and collaborative team science project consisting of graduate students, postdocs, faculty, research
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://www.simonsfoundation.org/neuroscience/simons-collaboration-on-ecological-neuroscience/(link is external) SCENE is a 10‑year, USD 80 million initiative funded by the Simons Foundation that aims to uncover how opportunities
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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
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QUALIFICATIONS: PhD in computer science, electrical/biomedical engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data