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Field
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experience of building energy simulation and/or urban building energy modelling (UBEM). Strong programming and data-analysis skills (e.g. MATLAB, Python or equivalent). Very good command of spoken and written
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atmospheric datasets using programming languages such as Python, MATLAB or R. Experience with atmospheric data processing, quality assurance and statistical analysis. A strong publication record of peer
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, spectroscopy) Data analysis, where programming (e.g., R, Python, Matlab) is considered a big plus Transferable skilss Open to learn and develop Pro-active and problem-solving mindset Ability to break-down and
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ML domains, such as deep learning, reinforcement learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g., TensorFlow, PyTorch), with evidence in
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. The ideal candidate holds a PhD in transport, operations research, civil engineering, or a related field, with strong skills in mathematical optimization and modelling (ideally in Python) and an interest in
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, or human-centered ML. ●Proficiency in programming languages (e.g., Python) and ML frameworks (e.g., TensorFlow, PyTorch), with evidence in the form of public (Github) repository. ●Excellent abilities in
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required to meet the eligibility criteria. Of secondary importance are: Experience with Python and relevant libraries for machine learning, optimization and simulation. Documented expertise in simulation
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in data processing, signal analysis, and programming (e.g. Python/Matlab) Demonstrated experience in publishing scientific journal papers Ability to work well independently as well as in a multi
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analytical and problem-solving skills. Experience with data analysis, numerical modelling or programming, for example in MATLAB, Python or similar tools. Good written and verbal communication skills in English
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. Experience with computational solid mechanics, computational soft tissue mechanics, or a closely related mechanics field. Well-developed coding expertise in Python, Julia, C++, Fortran, or a similar scientific