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models and/or probabilistic modelling, and excellent programming skills in Python and a modern deep learning framework (e.g., PyTorch or JAX) are required. Excellent skills in spoken and written English
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of the following areas will be beneficial. Experience with machine learning or data-driven modelling, particularly for chemical or process systems Experience with Python, or similar tools for data analysis and
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language (C++, Python, Rust, …) One high-quality first-author paper (journal or top-tier conference) You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research
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language (C++, Python, Rust, …) One high-quality first-author paper (journal or top-tier conference) You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research
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. Experience and expertise in human mobility simulation and prediction with agent-based modeling and deep learning techniques. Proficient in Python programming for geospatial data processing, modeling, and
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computing environments, such as Python, R, MATLAB or an equivalent tool, for data processing and analysis. good ability to work independently, formulate research questions and select appropriate methods. good
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discipline. Demonstrated experience in scientific programming, scientific software development, or data-intensive computing. Experience with Python and at least one high-performance programming language such
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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of cladding hoop stress and assessment of PCI-failure risk, • implementing, testing and documenting computational tools, for example in Python, and contributing to reproducible computational workflows
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environment. Particularly meritorious are experience with GPS or other mobility data, PPGIS, wearable data, environmental exposure modelling, longitudinal or repeated-measures data, and programming in R, Python