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Field
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data (e.g. instrumental, laboratory, environmental, numerical and categorical data, text, geospatial data or time series); c) Experience in Python programming and in data analysis and machine learning
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Skills/Qualifications Technical Skills: Advanced programming in Python, PyTorch, PyTorch Geometric or DGL. Version control (git), Linux and model training on GPU (reproducible experiments). Other
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the scenario literature on residual emissions, carbon dioxide removal and carbon capture and storage Proficient programmer, with experience in Python for data analysis (e.g. pandas, pyam) and reproducible
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quantitative and computational research. Good analytical and problem-solving skills. Experience or demonstrable potential in programming using Python, R, Julia, MATLAB, or a related language. The ability to work
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dormancy, persistence or stress physiology, bacterial defence systems, single-cell imaging, microfluidics, image analysis, Python or R would be advantageous. Appointment at Research Associate level is
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learn new things - A strong programmer who’s comfortable with Python - An open-minded thinker and precise communicator who enjoys collaborating with colleagues from a wide range of backgrounds and areas
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quantitative data and relevant software (Stata, R, Python, or similar) would be advantageous. This is a part-time (32% FTE, 12 hours per week) fixed-term post until 28 February 2027. The Department of Social
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, parabolic equations, ray-tracing. Skills: excellent computational skills: Python, Fortran, HPC. Language skills: Fluent in English, Spanish is not required but advantageous. Specific Requirements We
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Python and modern machine‑learning development, including version control (Git), testing, and reproducibility; experience with cloud-based solutions (e.g., Azure) is a plus. In our international working
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of relevant experience. Must have extensive expertise in computational modeling, including strong coding skills in Python. Strong statistical and mathematics background. Preferred Qualifications Merkin Bridge