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completed within the last 5 years or expected to be completed soon. Expertise in AI/ML methods in an environmental or Earth science context Experience programming in Python or related languages A strong
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or CP2K on massively parallel architectures. Solid skills in common scientific programming languages, in particular languages such as FORTRAN, C, C++, and Python Experience in parallel programming with one
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research on perovskites and/or organic semiconductors Demonstrated experience in global and deconvoluted data fitting, programming in Python and Matlab, as well as electronic structure modeling Intercultural
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computing environments, such as Python, R, or MATLAB; A strong publication record appropriate to the candidate’s career stage; The ability to work both independently and collaboratively in
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experiments. Utilize laboratory techniques that support hypothesis-driven neuroscience research. Analyze and Interpret Data Process, interpret, and visualize scientific data using tools such as R, Python
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fitting, parameter estimation, and model comparison Proficiency in at least one scientific programming language (e.g., Python, MATLAB, R) Demonstrated ability to work independently while collaborating
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Engineering, Applied Mathematics, or a related field. Candidates should have expertise in several of the following areas: Scientific software development (C++, Julia, Rust, Python, or similar) Numerical methods
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particular text and/or image analysis and platform data Interest in topics related to political communication Knowledge of Python and/or R Strong quantitative analysis skills Teaching experience Excellent
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/ experience in e-learning (TARGET CRITERION) IT skills (Office products, data evaluation, Python) (TARGET CRITERION) Team player and high social/communicative skills (TARGET CRITERION) Knowledge of MIP
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field. Demonstrated experience with satellite remote sensing for large-scale vegetation or forest monitoring, including Landsat and/or Sentinel-1/2 time series. Strong proficiency in Python for geospatial