64 distributed-computing-associate-professor Postdoctoral research jobs at Stanford University
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Posted on Tue, 01/21/2025 - 07:48 Important Info Deprecated / Faculty Sponsor (Last, First Name): Wang, Sophia Stanford Departments and Centers: Ophthalmology Appointment Start Date: ASAP Group or Departmental Website: http://optima.stanford.edu (link is external) How to Submit Application...
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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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Mathematics, Physics, Engineering, or Computer Science. This is a collaborative, cross-functional team, and project assignments will be tailored to match each postdoc’s strengths and growth goals. If you are
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team with other lab members. Our lab is an inclusive space that fosters learning & curiosity, promotes team work and values mentorship to drive an innovative research program that pushes the boundaries
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available immediately in the Molecular Imaging Program at Stanford (MIPS). The successful candidates will join a dynamic research group focusing on the development of peptide-based therapeutics and
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generation technologies Preparing quarterly and final reports for research grants Writing research proposals, peer-reviewed publications, and other program activities. Advising and mentoring students
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experience using mouse models of disease. Priority will be given to applicants with prior training in pulmonary biology, or candidates with expertise in computational biology or single cell transcriptomics
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, Applied Mathematics, Statistics or related computational field. Superb quantitative background, strong coding skills (e.g., Python, R). Expertise in infectious disease modeling. Strong record of peer
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work on a priority research program in which individuals are assessed with functional MRI, behavioral, and symptom measures before, during, and after treatment. Treatment includes selectively targeted
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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