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Field
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to conduct research on two interdisciplinary research projects on transportation, environment, and health. The candidate is expected to work on data integration and fusion, develop theoretical and mathematical
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to build a collaborative scientific carrier in computer science and medical data analysis at a German top-ranked university. Help to acquire, mentor and teach students (e.g., PhD, MSc, BSc, seminar series
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experience (possibly as part of the PhD) in a field related to mathematical analysis of partial differential equations (PDEs), calculus of variations, optimal control, who is willing to engage in innovative
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Behavioural competencies Education You should have recently completed, or be close to completion of a PhD in computer science, mathematics, or informatics, with the subject of your thesis being relevant t
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. Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning
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06.09.2021, Wissenschaftliches Personal The Institute for Communications Engineering is currently offering seven positions for PhD or postdoctoral candidates for the project "6G-life" which is
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
Experience Requirements The post-doctoral fellow will have received a PhD, DrPH, MD, or equivalent doctoral degree with experience in environmental health, environmental chemistry, environmental engineering
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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
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University Munich (www.tum.de). Accordingly, we are currently searching for PhD Students and Postdocs to join our team! PhD Students For PhD students, we are looking for persons that are willing to learn and
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, enrichment analyses - biological interpretation of data Your qualification - PhD/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq