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Field
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platform and provide Python/Jupyter-based tools for collaborators, contributing to FAIR datasets and open-source software (Co-)Supervise student projects at BSc, MSc, and PhD level Write research articles
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learning pipeline in Python (using e.g. PyTorch) - validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) - publication and presentation of your
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algorithms are desirable. Strong programming skills (C/C++, Python; hardware-description languages “e.g., HLS, VHDL” is a plus). Motivation to pursue a PhD and contribute to applied AI research. Excellent
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, information science, sociology, communication science, political science, linguistics, physics Very good knowledge of R and/or Python Experience in the use of machine learning and natural language processing in
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pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results
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, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language skills, ability
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degree in computer science, mechatronics, or electrical engineering. Strong programming skills (C/C++, Python; hardware description languages such as HLS or VHDL are an advantage). Knowledge of computer
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such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in
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-ray scattering, materials science, and/or experimental methods at large-scale research facilities Experience in scientific programming (e.g. Python), data analysis and handling/managing large datasets
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. Knowledge of geoinformation technologies, 3D building modelling (BIM), and AI applications Knowledge of R and Python—especially spatial data science techniques Analytical and process-oriented thinking as