34 machine-learning Postdoctoral positions at Princeton University in Ireland-University-Ranking-2024
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: 285829862 Postdoctoral Research Associate - AI/machine learning for biochemistry Location: Princeton, New Jersey Salary Range or Pay Grade: $65,000-$70,000 Description The Skinnider Lab at Princeton
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and machine-learning potentials for planetary materials. Curating and generating large-scale ab initio datasets across wide pressureâ“temperature regimes. Designing and training advanced machine
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searching for a computational postdoctoral research associate. The project is associated with atomistic plasma-surface interaction simulations, employing machine learned interatomic potentials (MLIPs
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: 286084265 ***REVISED*** Postdoctoral Research Associate Location: Princeton, NJ Salary Range or Pay Grade: 65,000 Description The Department of Electrical and Computer Engineering invites applications
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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational methods to discover unknown metabolites that have strong associations to experimental
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the application of statistics and machine learning in social science. The position requires no teaching, though teaching opportunities may be provided if requested. When teaching, successful candidates will carry
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science -electrical or computer engineering -genomics -neuroscience -population genetics / genomics -sociology Expected Salary Range: Salary begins at $65,000/year and will be commensurate with experience
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: 285516906 ***REVISED*** Postdoctoral Research Associate Location: Princeton, NJ Salary Range or Pay Grade: 65,000 Description The Department of Electrical and Computer Engineering invites applications
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the faculty director to share their work, and monthly meetings with faculty fellows from various social sciences to present their work and learn from others. Fellows are also encouraged to engage with