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or Python Life cycle assessment (LCA) Software related experience on system dynamics modelling, GIS, and energy simulations Research writing and publications Applicants must fulfill the eligibility and
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
proficiency in Python is required, and hands-on experience with ML libraries such as PyTorch is expected. Theoretical understanding and experience with multi-physics modelling of electrochemical processes can
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welcome candidates with a Master’s degree in (computational) chemistry, physics, or materials science who are curious about applied machine learning in the natural sciences. Prior machine learning or Python
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of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in the design and implementation of Open Science/Open Source practices
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development (experience in multiple fields are considered beneficial). Familiarity with simulation software and numerical methods and proficiency in programming languages (Rust, Python, MATLAB, C/C