21 machine-learning-modeling-"LIST"-"CEA-Saclay"-"Humboldt-Stiftung-Foundation" positions at Princeton University
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 277494287 Position: Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in
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coupled discharges employed in plasma processing, coupled with a proven track record of kinetic modeling of such discharges. The candidate should be familiar with machine-learning principles for science
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following topics: Machine Learning for Digital Twins, Foundation Models, and surrogates (surrogate model building from our suite of fusion codes, new optimization techniques, and differentiable programming
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of research that PPPL supports are the following topics: Machine Learning for Digital Twins, Foundation Models, and surrogates (surrogate model building from our suite of fusion codes, new optimization
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used in DA systems. Experience with machine learning is also welcome. Selected applicants will be expected to work in a collaborative environment, adhere to best software and data practices, write
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Seeking a temporary Research Associate in machine learning. Pursue research in machine learning. Work on new forms of diffusion-based generative models. Meet with postdocs Participate in group
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and events. Strong computer skills, comfortable using a variety of software, with the confidence and ability to learn new systems. Flexible work schedule required which will include hours on Saturdays
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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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, 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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understanding of and attention to information security in a world-class institution of teaching, learning and research. The CISO works collaboratively with University leadership and departmental technical and