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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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2019 https://doi.org/10.1038/s41596-018-0110-x and Lara et al., arXiv:2503.21396 https://doi.org/10.48550/arXiv.2503.21396 )). In parallel with your experimental work, you would develop theoretical
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process, and subsequently implement this infrastructure on top of an existing cloud infrastructure. You will play a key role in the project's development, ensuring technical tasks and teams work together to
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screening (e.g., luciferase assays, high-content imaging, massively parallel/multiplexed assays, etc.) is desirable. Ability to interpret and discuss experiments and critically contribute to writing
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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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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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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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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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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
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific