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modern models beyond the worst case e.g. integrating machine learning into algorithm design. We are looking for candidates with a strong mathematical background, an excellent degree in mathematics
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of Physics by means of various spectroscopy schemes and also at Q.ANT in their gyroscope/magnetometer labs. With this thesis, the PhD student will acquire broad knowledge on state-of-the-art laser technology
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of computational approaches to large scale simulations Basic knowledge of (geo)chemical processes and machine learning will be of advantage Expertise in Machine Learning approaches, ideally beyond neural networks
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new approach for microelectronics technology, this project teams up materialists, electrical engineers, and computer scientists of Forschungszentrum Jülich, TU Dresden University, RWTH Aachen University
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new approach for microelectronics technology, this project teams up materialists, electrical engineers, and computer scientists of Forschungszentrum Jülich, TU Dresden University, RWTH Aachen University
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new approach for microelectronics technology, this project teams up materialists, electrical engineers, and computer scientists of Forschungszentrum Jülich, TU Dresden University, RWTH Aachen University
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range of methods, including survey psychology, response-time paradigms, process-tracking techniques (mouse-tracking, eye-tracking), and incentive-based behavioral paradigms and experience in (learning
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mathematical modeling to simulate water fluxes and biogeochemical processes related to carbon and nitrogen cycling in the soil-plant system Experience with Bayesian inference and machine learning is an asset
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– but it is a great opportunity for you to learn German! The historic city of Göttingen, located in the heart of Germany, offers great outdoors and cultural opportunities, a vibrant student scene, and an
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results or willingness to acquire such experience very good knowledge of MS Office, including Word, Excel and PowerPoint very good written and spoken English skills self-motivated, independent and