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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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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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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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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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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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of XYZs, higher order perturbative calculations inside effective field theories. The particle and nuclear theory group at the TUM School of Natural science is lead by Prof. N. Brambilla and Prof. A. Vairo
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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
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-leading centre for research in acoustic engineering. The IoSR is also home to the world-renowned Tonmeister degree, which has produced a stream of highly successful graduates who have collectively received
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 3 months ago
Institute for Multidisciplinary Sciences Department NanoBiophotonics Prof. Dr. Stefan W. Hell Am Faßberg 11 37077 Göttingen Germany
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Prof. Daniel Merkle. The overall research project is based on the novel application of formalisms, algorithms, and computational methods from computer science to the design of microbial communities