12 computer-programmer-"the"-"IMPRS-ML"-"IMPRS-ML"-"Prof"-"UCL"-"U" "Dr" PhD positions at Leibniz
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science foundation (DFG). Doctoral students (m/f/d) are facilitated to participate in the doctoral program in order to successfully complete their dissertation. We offer an attractive workplace with
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will be given the opportunity to develop a doctoral thesis with extensive support through the CBBS graduate program (https://cbbsgp.med.ovgu.de ). Your profile: MSc in Neuroscience, Biology, Biomedical
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; German would be desirable Initiative, motivation, commitment, and scientific curiosity We offer a structured PhD program, exciting research topics, a stimulating international environment, a good
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computational approaches Beyond technical training, you will join a dynamic, collaborative and international team and receive structured support through our PhD training program. Your Profile: Master’s degree
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functionalities. This highly collaborative project, jointly investigated by PDI, TU Munich, University of Münster and HTW-Berlin, is funded by DFG within the priority programme SPP2477 "Nitrides4Future
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. This highly collaborative project, jointly investigated by PDI, TU Munich, University of Münster and HTW-Berlin, is funded by DFG within the priority programme SPP2477 "Nitrides4Future". The motivation is to
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standards in biodiversity text analysis Disseminate research results through peer-reviewed publications, academic conferences, and collaborative research proposals Your Profile MSc in biodiversity informatics
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to develop long term, quantitative strategic plans that emphasize sustainable agribusiness enhancement. This PhD position is carried out in collaboration with the Doctoral Program in Agricultural and Forestry
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-performance computing and imaging facilities. a collegial, international atmosphere and flexible, family-friendly working hours a structured PhD programme with extensive training and career-development
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta