280 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "INESC ID" positions at DAAD
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Gilman International Scholarship Program“ DAAD provides up to 40 additional „Gilman-DAAD Scholarships“ per year for U.S. undergraduate students to study and/or intern in Germany. Only US Pell Grant
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available in the further tabs (e.g. “Application requirements”). Programme Description The one-year scholarships are intended for graduates from Bulgaria, Croatia, Czechia, Hungary, Poland, Romania, Russia
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Description KIT Graduate School Computational and Data Science (KCDS) is a graduate school at KIT Center MathSEE that offers an interdisciplinary training program for doctoral researchers in
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available in the further tabs (e.g. “Application requirements”). Objective The aim of the programme is to support young scientists and academics in Aceh in the aftermath of the 2004 tsunami and help promote
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are among others: above average academic performance personal suitability for the programme and its objectives knowledge of the German language (at least level B1) good command of English The selection
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available in the further tabs (e.g. “Application requirements”). Programme Description How can digitalisation contribute to a more sustainable future at a time when global climate change is challenging our
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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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60% of the coursework in their degree program. What can be funded? A study semester at a German university, followed by a 4 to 6 month internship in a German company Duration of the funding 12 months
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environment Motivation and self-discipline to carry out research independently Willingness to work on numerical and experimental tasks Programming skills (e.g., Matlab, SIMULINK, Python) or other common process
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science, applied mathematics, physics or a similar area very good programming skills in Python good prior experience with neural networks using common Python-ML libraries such as PyTorch preferably also background