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Postdoctoral Affairs. The FY25 minimum is $76,383. Position is FILLED The Stanford Optima Group is seeking a highly motivated and skilled postdoctoral researcher to lead machine learning projects investigating
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and aggression, using optogenetics, in vivo imaging, electrophysiology, and sophisticated machine learning/artificial intelligence analyses of mouse behavior. All projects have translational components
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from varied sources, and machine learning methodologies Required Application Materials: 1. A cover letter describing: a. Your interest in this position b. Your relevant training and experience c. Your
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to) the qualifications of the selected candidate, budget availability, and internal equity. Pay Range: $86,100 Aligning Machine Learning Models with Algorithmic Reasoning Tasks We are seeking a postdoctoral researcher to
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focuses on translational research at the intersection of bioelectronics, healthcare-focused nanofabrication, and emerging applications of machine learning in radiology. Our team operates within a state-of
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transcriptomics analysis • Interest in cancer biology and immunology principles • Excellent written and verbal communication skills Preferred Qualifications: • Experience with machine learning approaches
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research on computational linguistics, machine learning, practical applications of human language technology, and interdisciplinary work in computational social science and cognitive science. The Stanford
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machines that both learn from humans and help humans learn. The postdoctoral fellow will lead a project using AI technologies to support active learning in young children, by empowering them to create
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, or machine learning experts to create predictive virtual 3D mammalian embryos for human health, especially congenital heart diseases. We welcome applicants with expertise in genomics, developmental biology
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understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. Responsibilities: Conduct research on the mechanisms underlying