10 parallel-and-distributed-computing-phd Postdoctoral positions at University of Tübingen
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and addresses Solidarity with Ukraine English in everyday university life Study in Tübingen Back Degree-seeking students International PhD candidates Erasmus and exchange to Tübingen Summer courses and
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. Requirements for employment are a completed PhD degree in a relevant field (computational linguistics, computer science, cognitive science, or similar), near native-level of spoken and written English, and
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well as data collected during the project. Experience in computational modelling is an asset. The activities of the research group are closely connected to the Tübingen Center for Digital Education (TüCeDE
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program within the GreenRobust Cluster of Excellence, and access to first class instrumentation and facilities. The PhD students will be part of an interdisciplinary PhD school with a structured supervision
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development and perform moderate teaching duties. Applicants are required to hold a PhD in physics or an equivalent doctoral degree. Applicants should provide a curriculum vitae, a list of publications, a brief
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International PhD candidates Erasmus and exchange to Tübingen Summer courses and short-term programs Advice and counseling for international students Studying abroad Back Ways to go abroad Erfahrungsberichte
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. The candidate should have: a PhD in microbiology, molecular biology, biochemistry or related subjects strong interest in genome-wide functional genetic methods, such as transposon or CRISPR assays. Previous
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and others) Analysis of the experimental data, ideally connecting to our machine learning tools Presentation of scientific results on conferences and in publications Requirements PhD degree in physics
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. Applicants should have a background in population genetics/genomics, molecular ecology, biodiversity informatics, or a related field. Experience with large-scale data analysis is essential. Additional
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adaptive systems that jointly optimize morphology and control for real-world physical interaction. Requirements Ph.D. in Computer Science or a related discipline. Strong background in Machine Learning