145 optimization-nonlinear-functions Postdoctoral positions at Princeton University in United-States
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) with expertise and interest in Large Language Models (LLM) for Energy Environmental Research and Applications. The researcher(s) will work with the principal investigator and team to develop, fine tune
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at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year appointments. Salary and full
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pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year appointments. Salary and full employee benefits are offered in accordance with Princeton
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, or the local vicinity, to fulfill responsibilities relating to in-person participation, office hours, and the like. The work location for this position is in-person on campus at Princeton University. They may
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rank are for one year with the possibility of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year appointments.Essential
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on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year
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related to exoplanets and AI, interstellar medium/star formation, gravitational dynamics, plasma astrophysics, and theoretical astrophysics. Applicants may work with the Department's distinguished faculty
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, or mechanobiology, strong organizational and communications skills, and be prepared to work in a dynamic environment. Candidates should apply online and include a cover letter, CV (including a list of publications
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. The Term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance and continued funding; those hired at more
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related field are particularly encouraged to apply.We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular