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. Qualifications Required Qualifications PhD in Computer Science, Materials Science, Physics, Chemistry, Geosciences, or a related field. Strong background in machine learning, scientific computing, or computational
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Science and Engineering Dynamics and Controls Systems Energy and Climate Fluid Mechanics Lasers and Applied Physics Materials and Mechanical Systems Robotics. This position is not eligible for sponsorship
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for Energy, Environment and Sustainability *Optical Materials and Light Matter Interactions *Quantum Materials Science Qualifications A PhD in Materials Science, Optics, Physics, Chemistry, Electrical
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and continued funding; those hired at more senior ranks may have multi-year appointments. Requirements include a Ph.D. in engineering, applied physical sciences or related areas and an experience in
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stakeholders involved in planning and decision-making. Qualifications Candidates must have a PhD in atmospheric physics, hydrology, meteorology, Earth system science, climate studies, applied mathematics
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of existing AI/ML tools to assign structures to unidentified peaks in metabolomic datasets (e.g., https://www.nature.com/articles/s42256-021-00407-x ), and extending these tools or developing new models as
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and research staff. For a full list of department members and activities, see https://web.astro.princeton.edu/. There are also strong research groups with interests in astrophysics at the Princeton
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matter, mathematical, and particle physics. Candidates for the position should have a Doctorate degree in Physics or a related discipline. To apply online, please visit https://puwebp.princeton.edu
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particle physics. Candidates for the position must have a Doctorate degree in Physics or a related discipline. To apply online, please visit https://www.princeton.edu/acad-positions/position/38722 and submit
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physical processes (e.g. ocean warming and mass redistribution); 2) conducting sensitivity analyses to identify the roles played by model forcing, horizontal resolution, and ocean-physics representation in