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need strong Python programming skills and experience with at least one major deep learning framework such as PyTorch, TensorFlow, Keras, MONAI, or similar. Experience in image analysis, video analysis
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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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polarization states. • Data Analysis & ML: Develop Python/MATLAB machine learning algorithms to map photocurrents to full Stokes parameters, targeting a reconstruction error of \(<1\%\). Required
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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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for Languages (CEFR). Knowledge of Python programming. Knowledge of JavaScript. Practical experience in artificial intelligence, machine learning or deep learning, in academic or business environments. Training
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statistical software including Stata, R or SAS, python. Have an emerging publication track record with high impact publication(s) within biostatistics, cancer and health services research or another related
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-on programming skills in R and Python, acting within server-side development environments such as RStudio, JupyterLab, and RSConnect, and will document development decisions and contribute to knowledge-sharing
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. • Excellent Python programming skills and strong hands-on experience implementing, training, and evaluating deep-learning models and research codebases. A strong track record in machine learning or closely
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software that allow time-evolving models of complex systems to be calibrated against sparse, indirect, and uncertain observations. The group develops and maintains an open-source Python framework