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research tackling questions on the perception of time and space in virtual immersive environments Solid quantitative skills (R, Python, or Stata) Programming ability relevant to your target position: hands
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skills Proficiency in at least one programming language for geospatial analysis: Python (rasterio, geopandas, scikit-learn), R or Google Earth Engine. Experience with open-source tools (QGIS, GRASS GIS
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the long term. Depending on the candidate’s background, the role may focus more on embedded software and firmware for low-level devices, or more on higher-level Python-based control software, automation and
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training and release decisions, keeping results consistent between training and serving. This role requires strong Python engineering, hands-on LLM evaluation experience, and the ability to work
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, produce quantised variants, and make sure each release works out of the box for the community. This role requires strong Python and software engineering skills, experience with LLM inference stacks, and a
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or projects) Experience with high-frequency transport experiments at low temperatures Proficiency in computer-based data acquisition and processing (e.g., Python, C++, LabView) Proven track record of high
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the translation of ecological science into decision-making. Experience with quantitative analysis, modelling, simulation, or programming, preferably in R, Python, NetLogo, Julia, or comparable tools
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systems, including command-line interfaces Practical knowledge of at least one programming language (C++, C#, Java, Python) and tools such as Git Responsible and informed use of AI-assisted tools in a
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language, such as Stata, R or Python The ability to communicate your ideas clearly in written and spoken English and German An interest in developing both independent and collaborative research projects and
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solvers, FDTD/FEM, coupled-mode theory, or PDE/ODE solvers) Interest in electromagnetic wave propagation, photonics, or semiconductor physics Experience with scientific programming and data analysis (Python