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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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of novel algorithms, machine learning for parsing biological data sets (genomics, proteomics, imaging, neuroscience), and related areas at the interface of computer/data science and the life sciences
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applications in machine learning. The ORFE department is part of the School of Engineering and Applied Science which is pursuing several initiatives in related areas.To be successful, the candidate must have a
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beyond ITER with advances in HTS materials, manufacturing, sensors and machine learning. High current density cables are required for the design of compact HTS magnets in a fusion pilot plant (FPP
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multidisciplinary collaboration, scholarly advancement, and the creation of tools and public goods.RequirementsApplicants must have (or expect to have at time of appointment) a PhD in the social sciences, statistics
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research associate positions broadly in statistics and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu ). The position is for one year with the possibility of reappointment
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: 278964401 Position: 2025 Postdoctoral Research Associate - AI/machine learning for analytical and forensic chemistry Description: The Skinnider Lab at Princeton University aims to recruit a postdoctoral
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vision and novel applications of machine learning. Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL dialect is preferred. Apply online at https
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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beyond ITER with advances in HTS materials, manufacturing, sensors and machine learning. High current density cables are required for the design of compact HTS magnets in a fusion pilot plant (FPP