145 programming-"the"-"DAAD"-"UCL"-"FEMTO-ST"-"IMPRS-ML"-"U"-"https:" "Prof" positions in Germany
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related field Demonstrated experience in geospatial analysis (GIS) and proven skills in hydrogeological or hydrological modeling Proficiency in programming (e.g., Python) Ability to handle large datasets
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international research network in the field of educational research with an integrated PhD training program. The successful candidate is expected to specialize in research methods (potential areas of expertise
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day-to-day basis and regularly report progress to Prof. Dieter Jaksch - contribute to the writing of project reports as required and assist with other administrative duties, as necessary
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atmospheric water cycle. Experience in data analysis using Python, R, or a comparable programming language, as well as in statistics. Fluency in English and the ability to work in a team. For further
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at Max-Weber-Platz with very good accessibility by public transport such as the subway, S-Bahn or tram Company pension plan through the Federal and State Pension Institute (VBL) Self-realization through a
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, or multimodal architectures, Strong programming skills in Python, with experience in Machine Learning and Linear Algebra Libraries (preferably PyTorch, also JAX, TensorFlow). Experience in CUDA programming is
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. The fellowships are funded by the state of Lower Saxony and are part of a joint doctoral program with the state of Baden-Württemberg on the evolution of cultural modernity. Requirements for filling the positions
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programming languages such as Python and experience with deep learning frameworks (e.g., PyTorch, TensorFlow) is highly desirable strong interest in interdisciplinary research combining imaging, machine
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programming skills in Python and/or C/C++ ability to work independently and collaboratively in an interdisciplinary environment excellent communication skills in English willingness to travel regularly between
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. Our program focuses on understanding hostpathogen interactions across species (mice, chickens, pigs, dogs) using well-established viral (e.g., Marek's disease virus, Theiler virus, Hepatitis E