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Python programming skills are required, and prior experience with developing open-source software or databases will be considered a plus. Candidates should apply at: https://puwebp.princeton.edu/AcadHire
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downconversion layer Analysis of data using software tools such as MATLAB, Python, or Origin. The candidate must be familiar with materials studio software and any other materials modeling software. Experience in
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scientific discipline. Experience in developing and running an atmospheric transport model. Experience in interpreting data. Experience with FORTRAN and Python computer languages. Proven ability to work
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implemented in the Fortran programming language, and it relies on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use
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. Knowledge of programming languages (e.g., C, C++, Python, R, Matlab) is preferred. Primary Responsibilities: The successful candidate(s) will be expected to carry out research under minimal supervision
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; proven competence in programming methods like Python; evidence of working well as part of a multidisciplinary research team. Informal enquiries may be addressed to Professor Tingting Zhu (email
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of field campaigns, data collection and lab work, Spectral data analysis, data processing, and model development, ‘R’, Python programming / package development, Co-supervise PhD and undergraduate students
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Language Models (e.g. Llama3, and Phi4) and Commerical models (e.g. Claude 3.7 and Gemini 2.5) to develop methods for generating simulation models of healthcare pathways in Python. The Health Service
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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fractionation (i.e. surface biotinylating, gradient centrifugation, and be proficient in advanced data analysis (i.e. R, Python). Excellent analytical, organisational, and problem-solving skills are essential