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Field
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modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected
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Postdoctoral Associate | Mitochondrial Genomics | Lake Lab — Yale University, Department of Genetics
high-throughput screens, and building novel cellular models to reveal mechanisms of mitochondrial genome dysfunction. The lab is located in the Yale School of Medicine which offers an outstanding
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responses. Structural Bioinformatics & Biophysical Modeling: Protein structure prediction (e.g., AlphaFold, RoseTTAFold, ESMFold), molecular dynamics (MD) simulations, or protein-protein/antigen-antibody
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semiconductor devices and circuits based on fully depleted silicon-on-insulator (FDSOI) technology for next-generation AI hardware. This position focuses on the design, fabrication, characterization, and modeling
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modeling; A solid understanding of molecular simulations, especially in relation to RNA systems, and capable of handling largescale biological data; Ability to communicate scientific concepts, analytical
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: the process modelling and development of CO2 hydrogenation to methyl formate, and the reaction engineering and kinetic analysis of alkylamine synthesis. Your responsibilities include: Reaction optimization
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(e.g., scRNA-seq) to investigate cellular heterogeneity, host-pathogen interactions, and immune responses. Structural Bioinformatics & Biophysical Modeling: Protein structure prediction (e.g., AlphaFold
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exoplanet candidates identified by space missions such as TESS and PLATO. This includes false-positive screening and the refinement of transit parameters. The telescope is currently being upgraded with a new
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laboratory workflows. The position will focus on building the data resources, predictive models, and closed-loop decision frameworks needed to accelerate experimentation and advance next-generation autonomous
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containment. The prohibitively high computational cost of such simulations necessitates the development of efficient and robust surrogate models for general GCS modeling tasks, especially when inverse modeling