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physical environments. This position focuses on research at the intersection of computer graphics, generative AI, and robotics, encompassing topics such as generative modeling, reinforcement learning, multi
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[map ] Subject Areas: High Energy Physics / BSM , BSM new physics , Dark Matter , Electroweak Symmetry Breaking , Experiment , Experimental , Flavor Physics , Higgs physics , LHC , Machine Learning
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Certificates/Credentials/Licenses N/A Computer Skills MS Office and willingness to learn software used in the research lab Supervisory Responsibilities No Required operation of university owned vehicles No Does
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humanistic questions. We anticipate that the Postdoctoral Associates will teach one seminar per year, which is one section of SHUM 2750 Introduction to the Humanities in the spring term. As well, we expect
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underlying various biological networks. The systemic dynamics team aims to develop digital medicine for sleep disorders based on health-wearable devices via mathematical modeling and machine learning. In BIMAG
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manufacturing principles. Experience with machine learning methods and integration into hybrid modelling systems Demonstrated ability to clearly communicate research concepts and results in high-quality journal
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profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning
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at https://puwebp.princeton.edu/AcadHire/position/40281 and submit a current curriculum vitae, research statement, and a cover letter. Contact information for three references is required. To learn more
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, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar). Experience with data
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-fidelity finite element models to investigate surface wave propagation in soft biological tissues, forming the foundation for subsequent statistical and machine learning frameworks that integrate