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Field
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judged from published papers or publicly available (e.g., arXived) preprints, will be given priority. Strong programming skills in R/Python/MATLAB with some knowledge of C/C++ will be preferred. Prior
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Bayesian statistics, stochastic modeling, and optimization under uncertainty • Proficiency in Python programming • Strong interest in applied and transferable research • Knowledge of industrial simulation
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required (e.g., Python, Mathematica, Matlab). Some knowledge of nonequilibrium statistical mechanics (Boltzmann and Vlasov equations) and magnetism (spin dynamics, Landau-Lifshitz-Gilbert equation) is
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Python and Matlab (at minimum). Be fluent in English, both spoken and written. *The date on your doctoral degree certificate is considered the official date of completion. Exceptions to the three-year
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knowledge of C++, Python, and R. Who we are At the Department of Agroecology, our main goal is to contribute to sustainable solutions to some of the world’s biggest problems within the areas of soil, plants
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for those who can also program in Python and know standard network analysis techniques and metrics such as community detection and centralities. Prefernce for those with experience in geo-spatial analysis
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collaboratively within a team Excellent written and verbal communication skills Proficiency in molecular bench skills and/or data analysis. Preferred to have familiarity with R, Python, or related scientific
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-disciplinary team in advancing applied research in 3D deep learning and forest science programming experience in Python and experience using deep learning tools such as PyTorch, Keras and/or Tensorflow ability
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experience in scientific data visualization, AI/ML, or a related field. Proficiency in the Python and C++ programming languages. Preferred Qualifications: Strong publication record with publications in
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and/or distributed systems techniques. • Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and parallel computing. • Demonstrated hands