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(at least finished before July 2025) very good programming skills and AI/ML knowledge good written and spoken English skills (CEFR level C1 or higher) We offer: cutting-edge research in data science and
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the programme as a tandem Academic Requirements predocs: graduates (Master's, Diploma or State Examination) from a German or international university in the transition phase at the end of their university studies
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supports studies in subject areas with strong relevance to national development. The scholarships at UGM are available in the following fields: Master Programme in Geological Engineering Female applicants
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first academic degree if applying for a Master’s programme, who want to pursue Master’s courses, at the Asian Institute of Technology (AIT). What can be funded? The In-Country/In-Region Scholarship
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of responsible electronics in an ecologically, economically, and socially sustainable manner. In a range of research and academic programs, REC² unites the natural and engineering sciences with the humanities
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) of the German Academic Exchange Service (DAAD). The structured graduate program is one of the core areas within the Munich Medical Research School (MMRS) and embedded in the Pettenkofer School of Public Health. A
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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available in the further tabs (e.g. “Application requirements”). Objective The programme aims at fostering strong, internationally oriented higher education systems in Southeast Asia with the capacity
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Requirements Applicants are enrolled in a Bachelor’s programme at a German institution of higher education, college of art or music (humanities, economic sciences or STEM disciplines), and have not yet completed
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project work plan and milestones Your profile Completed university studies (Master/Diploma) in the field of Chemical/Metallurgical/(Mineral) Process Engineering, Data Science, Statistics, Machine Learning