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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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: 272265297 Position: Postdoctoral Research Associate Description: The Princeton Center for Statistics and Machine Learning (CSML) invites applications for DataX Postdoctoral Research Associate positions
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acids, ligands), coarse-grain and polymer model development, multiscale modeling, molecular simulation code/software (e.g., LAMMPS, GROMACS), machine learning. Prior experience with applying simulations
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, multiscale modeling, molecular simulation code/software (e.g., LAMMPS, GROMACS), machine learning. Prior experience with applying simulations to biomolecular systems is a plus but not required. Applicants
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of design, computation, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and
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, computation, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational
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The Princeton Center for Statistics and Machine Learning (CSML) invites applications for DataX Postdoctoral Research Associate positions. The DataX Postdoctoral Research Associate positions
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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion
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d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
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theoretical computer science and theoretical machine learning. The Term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory