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yeast Mif2/CENP-C promotes inner kinetochore assembly. Current Biology. https://doi.org/10.1016/j.cub.2023.01.012 (link is external) Drug Discovery: New Therapeutic Mechanisms In parallel, we use
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of first-author publications in reputable peer-reviewed journals Demonstrated self-initiative and motivation, ability to collaborate, organize parallel experimental workflows, and interpret and present
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the pharmacological industry; prospects for a career in academic or industry are high. In parallel with this effort, we are also working on anti Iglon-5, an HLA-DQ5 associated autoimmune disease
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define the molecular basis for their modes of action in bacterial cells. In parallel, we investigate how bacteria build and organize their cell surfaces, cell walls, and extracellular structures; how
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development Programming in Python, R, MATLAB, or related scientific computing environments Reproducible research practices, including version control, high-performance computing, and open science
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Health Initiative), and local Stanford data. Lab members have access to state-of-the-art computational resources, including cloud-based computing and Stanford high performance clusters. We offer
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‑performance computing cluster offer an unmatched playground for ambitious science. Key Responsibilities • Design, execute, and analyse high‑density electrophysiological recordings (e.g., Neuropixels) in
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of the following areas: atmospheric convection, radiative transfer, climate change, atmospheric/fluid dynamics, or machine learning. Proficiency in numerical analysis and high-performance computing
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-performance computing, and Stanford's broader ecosystem of core facilities. Required Qualifications: Ph.D. in structural biology, proteomics, biochemistry, life sciences, or a related discipline
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segmentation, feature extraction, signal quality assessment, artifact detection, or time-series modeling. Experience with Python scientific computing tools such as NumPy, SciPy, pandas, scikit-learn