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Mathjobs.org | about 1 month ago
-constrained inference, time series, and Bayesian analysis. In applied mathematics, these include information theory, coding theory, control theory, fluid mechanics, and mathematical biology. Further
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-constrained inference, time series, and Bayesian analysis. In applied mathematics, these include information theory, coding theory, control theory, fluid mechanics, and mathematical biology. Further
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, development of coding protocols, quality control of annotated datasets, statistical analysis, collaboration with the project's data specialist, publication of research findings, and participation in
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working at the intersection of AI, Game Theory, Economics, and Computer Science. We are seeking candidates with a Ph.D. in a quantitative field with a strong interest in building AI agents . Particularly
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should demonstrate experience of conducting and completing research from idea conception to publication and presentations, with experience in coding and data analysis. They should demonstrate excellent
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). The postdoc will perform enhanced sampling molecular dynamics simulations using neural network potentials and deploy statistical mechanics (e.g., rare-event theory), Markov-state models for molecular
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demonstrate experience of conducting and completing research from idea conception to publication and presentations, with experience in coding and data analysis. They should demonstrate excellent
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analysis and reproducible research. Experience with coding in Python. Preferred: Experience with latent variable models, item response theory (IRT), adaptive testing, or gamified assessments. This
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hands-on education in molecular genomics, population genetics, evolutionary theory, non-coding regulatory biology, and/or bioinformatics via their participation in research projects in the laboratory
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particularly welcome strong candidates from physics, engineering, computational science, or other areas of chemistry, with high motivation and strong theoretical/analytical/coding ability. Your opportunity We