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/scripting (e.g., in Python, and/or R, and/or Matlab, and/or Bash script & NCO & CDO, etc.) and have demonstrable expertise in the analysis of big data, while the experience with interpretation of climate
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atmospheric physics, meteorology, climate, numerical methods, and data science. The Research Associate will be proficient in programming/scripting (e.g., in Python, and/or R, and/or Matlab, and/or Bash script
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in C++ or Python. Affinity with education and logistics. A proactive, independent working style. Eagerness to work on achieving societal impact. A Certificate of Good Conduct (VOG) will be required
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, or industrial engineering. Proficiency in Python and simulation tools (e.g. AnyLogic, Arena) and optimization solvers (Gurobi, CPLEX). Solid background in decarbonization modeling, logistics, and techno-economic
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, energy systems, simulation, and/or transportation research. Technical skills: Python programming; simulation. Domain knowledge: Decarbonization modeling, life-cycle assessment, battery-electric vehicle
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have an interest in the use of AI in healthcare. Proven competence in programming methods in Python and similar environments is also essential. Informal enquiries may be addressed to Professor David
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methods in Python and similar environments is also essential. Informal enquiries may be addressed to Professor David Clifton (email: david.clifton@eng.ox.ac.uk). Only online applications received before
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: PhD in solar energy, electrical engineering, or environmental sciences. Proficiency in PV systems, instrumentation, and performance measurement. Experience in processing environmental data (Python, R
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and solids. Experience in scientific programming in C/C++, Python, Fortran, Mathematica or similar is required. The successful candidate will either hold a PhD in Physics or a related area, or
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., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer