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Description The Graduate School Scholarship Program(GSSP) of the German Academic Exchange Service (DAAD) is offering two (2) doctoral scholarships to earn a PhD within the framework of “Ancient
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machine learning We offer: Academic freedom to pursue your scientific interests related to infection biology, inflammation, gene expression, and intracellular organization Competitive salary including
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Time Span 01 Apr 2026 for 4 years Application Deadline 15 Dec 2025 Areas of study Development Co-operation, International Relations, Political Science, Developmental Psychology, Clinical Psychology, Psychology, Social Psychology, Business, Occupational, and Organisational Psychology,...
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on these topics. One position is in the "X‑Ray Nanoscience and X‑Ray Optics" group and the other is in the "Computational Imaging" group. The PhD projects are embedded in the frame of the ErUM data project CmarT
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Description For our location in Hamburg we are seeking: PhD student for information field theory and ptychography Limited: 3 years | Starting date: earliest possible | ID: FSDO017/2025 | Deadline
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international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities
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labs) Intensive scientific supervision and interdisciplinary collaboration within the project consortium Opportunity to pursue a PhD in cooperation with a German university A structured PhD program with
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Mathematics/ Approximation Theory to be filled by the earliest possible starting date. The Chair of Applied Mathematics, headed by Prof. Marcel Oliver, is part of the Mathematical Institute for Machine Learning
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shock factors in plants”: PhD student (f,m,div) in Plant Biology Reference number: 26/2025/1 The salary will be based on qualification and research experience according to the wage agreement TV-L, up
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techniques in both space and time (e.g., correlated APT, TEM, FIM, EBIC, EBSD, XPS Kelvin probe microscopy, machine learning augmented analysis techniques) Experimental and computational analysis of transport