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Field
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development, and publication in peer-reviewed venues. Strong background in machine learning, with research experience in deep learning, foundation models, or related areas. Solid programming ability in Python
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, and evaluation The ideal candidate will lead their own project, and also collaborate with and support 1-2 PhD students on their projects. The ideal candidate will also be interested in learning to write
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well as general research involving the application of methods from theoretical physics, mathematics, and machine learning with the goal to understand the brain function. Position Requirements Applicants
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, Machine Learning , Neutrino , Neutrino physics and Astrophysics , Phenomenology , Quantum Field Theory , Theoretical Particle Physics , theory , Lattice QCD Appl Deadline: 2025/12/02 04:59 AM (posted 2025
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related to learning engineering and AI in education, working with a team of postdoctoral researchers, PhD students, and Master’s/undergraduate researchers across multiple universities and organizations
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data issues. Utilizing machine learning techniques as appropriate for data analysis. Developing computing programs and software to support research initiatives. Applying new methodologies to real-world
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candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our
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Postdoctoral Associate / Senior Postdoctoral Associate Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD or MD or foreign equivalent in hand by date of hire
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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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