652 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" uni jobs in Germany
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research and work environment within a young and dedicated team · An exceptional opportunity to experience research in a highly inspiring international environment and to learn from some of the world's
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(specifically machine learning) in early drug discovery, precision medicine and clinical trials. The team is internationally well connected and is working closely together with leading European and US
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packages for machine learning. You are not afraid of learning new technologies and frameworks and enjoy developing prototypes. You are independent, creative and curious and you can work independently. What
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topics at Fraunhofer ITWM are machine learning, artificial intelligence, renewable energies, and sustainability. In addition, next-generation computing and quantum computing are future-oriented topics
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be achieved, for example, by developing learning algorithms and bringing together different sensor systems in the vehicle and on the road. Where you put the focus - that is up to you. The concepts
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at Fraunhofer ITWM are machine learning, artificial intelligence, renewable energies and sustainability. In addition, next-generation computing and quantum computing are future-oriented issues that our
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coding skills to design highly efficient algorithms. Solid knowledge in the areas of algorithmics, optimization problems, as well as experience with SAT/SMT solvers or machine learning is an advantage
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environmentally friendly chemistry, in applications for the aerospace and military sectors as well as in life-cycle assessments, recycling and sustainability concepts – which you could soon help to create
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outstanding researchers with a strong track record of advancing the state of the art in machine learning and potentially its application to biology and biomedicine, with the ambition to build an internationally
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Learning, especially in spatiotemporal modelling, environmental data analysis, or multimodal learning, Practical experience in applying Machine Learning, ideally including deep learning, foundation models