92 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Stanford University
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biology, bioinformatics, genetics, AI, machine learning, computer science, or a related field. Demonstrated experience analyzing single-cell and/or spatial genomics datasets is a plus but not necessary
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will have connections to both the Molecular Imaging Program at Stanford (MIPS) and the Radiological Sciences Laboratory (RSL). The ideal candidate for this position will have interest in being trained in
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computational frameworks that transform how we decode cancer biology from spatial multi-omics data. Our vision is to build foundation models for tissue biology, integrating spatial proteomics, spatial
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, California 94305, United States of America [map ] Subject Areas: Applied Physics Chemistry Materials Science Quantum Optics Computer Science (more...) Quantum Gravity quantum gravity/quantum cosmology Quantum
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(PhD, MD, or equivalent) conferred by the start date. Proven research and/or professional experience in machine learning and/or natural language processing, with a preference for prior experience working
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. • Develop computational and theoretical models that bridge neural data and behaviour, leveraging modern machine‑learning toolkits. • Drive multi‑lab collaborations across SCENE; co‑author high‑impact
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fellowships and NSF SBE postdoctoral awards. We especially welcome applicants with theoretical interest in child language development, strong computational and analytical skills (deep learning frameworks), and
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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings
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undergraduate course. The Fellow may not undertake any other sustained employment for the duration of their postdoctoral appointment. Applicants must have earned their PhD within the past 3 years. Advanced
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experience. Research background in decision making systems, in particular the use of different optimization, machine learning, and decision making modeling techniques for problem solving. Desire to grow