152 post-doc-in-wireless-communication-and-networks-2016 PhD positions at DAAD in Germany
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-year contracts at each institution (4 in total) are envisaged. The applicant will have to apply and be admitted to post-graduate study programme at the Faculty of Mathematics and Physics, Charles
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projects within the open call on “Molecular Mechanisms in Genome Stability & Gene Regulation”. As an IPP PhD student, you will join a community of exceptional scientists working on diverse topics ranging
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
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Description The Graduate School Language & Literature at Ludwig-Maximilians-University Munich (Germany) offers a doctoral fellowship (fully-funded for up to 4 years) for excellent international
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offer A vibrant research community in an open, diverse and international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a
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-on training in small groups, summer schools, networking events and hackathons/datathons. Send your application if you can see the potential in thinking simulations and data together and if you are ready to
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partner groups MPI Halle and Leiden University/NL. The successful candidates commit to actively participate in networking including regular research visits to the partner laboratories. Requirements
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mid-sized German institution accommodating approximately 18,000 students, is closely affiliated with numerous research institutes. It is part of the European university network YUFE–Young Universities
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adaptations to the environment, the development of distinct feeding strategies, communication, and other specialized functions. The head and face, including their specific shape, emerge during embryogenesis. We
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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