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the goal of obtaining a doctorate. It is based in the newly established Animal Neurophysiology group (Prof. Münch) at the Institute of Animal Physiology, at the Faculty of Biology and Chemistry. The salary
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science, e.g, by leading to more effective batteries. The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato
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but not essential. A strong background in materials science and/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition
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open, reproducible science. This exciting and challenging project will be jointly supervised by Prof Rossiter (Soft Robotics) and Prof Kent (Psychology) but will offer many networking opportunities and
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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-chemical-physics/ ) led by Prof. Alexandre Tkachenko at the Department of Physics and Material Science, we are looking for a PhD candidate to perform molecular dynamics simulations of different genetic
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Mathematics, Technomathematics, Computer Science, Engineering Informatics, Theoretical Computer Science, Physics Description Description The research group Cyber-Physical Systems of Prof. Matthias Althoff
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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally oriented
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field” imaging techniques to solve many important problems in biology and change clinical practice in respiratory medicine. Our ongoing research program involves developing new imaging technologies
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interdisciplinary research environment, where you'll work alongside experts from fields such as transport and urban planning, engineering, data science, computer science. Skill Development: Our extensive