102 computer-programmer-"Nova-School-of-Science-and-Technology" PhD positions at Nature Careers
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Marie Skłodowska-Curie Actions (MSCA) COFUND doctoral programme INNOCHEMBIO (https://taltech.ee/en/innochembio), which is co-funded by the European Union (Grant agreement 101217295), offers 15 PhD
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Programme description: The ICN2 offers a competitive PhD Programme to talented students who wish to develop a research career at one of the top European institutions in the field of nanoscience and
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the research school and learn alongside each other in carefully designed courses that align with the excellence centre’s multidisciplinary theme. The program prepares next-generation computational biologists
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academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and
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) Fluigent SA (FR) Thermo Fisher Scientific GMBH (DE) Harvard Medical School (US) The candidates will all be part of a strong Joint PhD training programme, with a focus on career development, application
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through the DKFZ International PhD Program and DKFZ Career Service Our Corporate Health Management Program offers a holistic approach to your well-being Contact: Prof. Dr. Dieter Saur Telefon: +49 89 4140
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projects are under the following three research programmes: Reconfigurable Systems research programme In this research programme we are: reimagining the use and reuse of materials themselves, for example
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of Biochemistry and Molecular Biology, which allows the candidate to tailor a flexible individualized course program Training in a wide range of scientific and transferable skills including research management
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Networks, and ICT Services & Applications. This industrial PhD position is part of the "Autonomous Systems for Land, Air and Space" (ATLAS) IPBG Programme co-funded by the FNR, SnT, and a consortium of
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient