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functional characterization center. The lab is especially interested in non-coding cis-regulatory elements (CREs) and the variation within them, using high-throughput experimental approaches such as
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) consortium as well as part of an ENCODE functional characterization center. The lab is especially interested in non-coding cis-regulatory elements (CREs) and the variation within them, using high
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conducting and analyzing molecular dynamics simulations Experience using high-performance computing platforms Experience developing neural network models Experience using AI-assisted coding tools for
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methods and bioinformatics tools for integration of multi-omics and gene regulatory networks. The long-term research goal is to answer the key scientific question “How non-coding genetic variant act
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this position will be to do excellent research at the borderland of behavioral, social, and computer science, both in collaboration with the Aalto team and within your existing professional network. We
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–sediment system. Opportunities to Contribute Develops dynamic river‑lake network models to assess geochemical and ecological changes—including carbon cycling and elemental fluxes—resulting from enhanced
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–sediment system. Opportunities to Contribute Develops dynamic river‑lake network models to assess geochemical and ecological changes—including carbon cycling and elemental fluxes—resulting from enhanced
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will have the opportunity to work with other researchers both at Stanford and within our larger national network of collaborators with similar research programs. Required Qualifications: Highly
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: expertise in programming and coding (preferably using Python and C++) and GUI development; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory and
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expected within 6 months. Demonstrated experience in in vivo two-photon imaging using calcium indicators in mice. Strong quantitative and analytical skills; prior coding experience (e.g., Python, MATLAB