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with Python and R programming languages. Experience with functional genomic technologies including massively parallel reporter assays. Biomedical informatics or biomedical research experience. Preferred
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parallel computing techniques including working in the cloud. Preferred Qualifications Education: No additional education beyond what is stated in the Required Qualifications section. Certifications
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parallel computing techniques including working in the cloud. Preferred Qualifications Education: No additional education beyond what is stated in the Required Qualifications section. Certifications
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
mathematics, or a related field Candidates should have expertise in two or more of the following areas: Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
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coarse- grained models of proteins within condensates). These topics share deep conceptual parallels. By advancing concepts in non-equilibrium statistical physics, the group aims to uncover the general
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chemical processes in complex condensed-phase systems, e.g., aqueous solutions, semiconductor interfaces, and polymers. These complex condensed-phase systems will be treated using first-principles machine
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closure modeling and/or high performance computing environments (MPI, CUDA) • Expertise in software development and computing tools (C/C++, python, git, parallel computing, etc.) • Experience with deep
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with ab initio methods. Proficiency in software such as VASP, Quantum ESPRESSO, Critic2 and Gibbs2. Experience in high-performance computing and parallel processing. Additional Qualifications Considered
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processes in internal combustion engines (ICEs), such as fuel injection, combustion, heat transfer, etc. Improve, develop, and implement CFD sub-models necessary to enable predictive ICE simulations
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platform enables us to test hundreds of different conditions in parallel and assess their impacts on human immune responses, such as antibody production. We routinely work with industry partners to exploit