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, they are primarily suited to stable environments and are less equipped to handle situations where the same place or action may have different spatial meaning or outcomes depending on context
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have: An MSc degree in Biomechanical Engineering or a closely related discipline by the start date of the position (September 2026) Experience in scientific programming (e.g., Python, Matlab) Experience
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enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present and communicate your ideas with AND without LLMs. You get excited about implementing your
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traffic flow theory and simulation. You are a machine learning enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present and communicate your
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the inversion problem to reconstruct environmental properties using received signals from a variety of EM wave sourcies located in different positions. Propose and implement computationally efficient solution
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up to 2050. Quantifying the environmental impacts of primary and secondary steel production under different future scenarios, including climate change, energy and resource use, water consumption, waste
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energy/water balance, evapotranspiration, thermal comfort, heat-health interactions. Solid programming and data analysis skills (e.g. Python, R, GIS). Willingness to travel for validation-related fieldwork
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deployment scenarios to evaluate future steel production pathways and circular economy strategies up to 2050. Quantifying the environmental impacts of primary and secondary steel production under different
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modelling is an advantage. Strong quantitative skills and interest in statistical modelling, or simulation approaches. Experience with R, STATA, Python or similar software. Ability to work independently and
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describing the electron optics of the projection column and optimize its performance through large-scale simulations. You will use commercial electron-optical simulation software but also develop custom Python