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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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big data and AI at its core. A central goal of the project is to build a foundation model of the visual brain—a “digital twin” that captures neural activity and intelligent behavior at unprecedented
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Posted on Tue, 03/04/2025 - 15:09 Important Info Deprecated / Faculty Sponsor (Last, First Name): Bohg, Jeannette Stanford Departments and Centers: Computer Science Postdoc Appointment Term: 2025
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learning to derive principled models of cortical computation. Our newly refurbished primate facility, state‑of‑the‑art Neuropixels rigs, and high‑performance computing cluster offer an unmatched playground
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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
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degradation capacity to cope with misfolded and aggregated proteins and characterize them in model systems of neurodegenerative diseases. Our goal is to develop nanobodies into mRNA-deliverable effectors
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would include: Co-developing a hybrid machine learning/process-based model of anaerobic digestion processes Performing techno-economic and lifecycle analysis of microgrids build around novel biogas-fueled
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. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will involve both method
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, molecular biology, and in vivo models. Analyze and interpret data, integrating experimental and computational findings. Utilize bioinformatics tools and techniques to analyze high-throughput sequencing data
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Center for Biomedical Informatics Research at Stanford University. This position emphasizes evaluating various cancer screening strategies by developing and applying microsimulation models for decision