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Collaborative Research Centre TRR 181 "Energy Transfers in Atmosphere and Ocean" | Kiel, Schleswig Holstein | Germany | about 6 hours ago
applicants hold a MSc or PhD degree in physical oceanography, meteorology, applied mathematics or a related field and are highly motivated to work in an interdisciplinary environment. The openings may be
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The project will involve rigorous error analysis and algorithm development. The candidate should ideally have a PhD in computer science, mathematics, or a related field, with background in one or more of the
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an outstanding record of promoting the public understanding of mathematics in diverse ways. Candidates should hold a PhD or equivalent and be able to demonstrate a strong record in research in
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Science at the B.S. level, Applied Mathematics, and Data Analytics at the M.S. level, and a doctoral concentration in Data Science & Analytics within the multidisciplinary PhD program in Applied Science and
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The Board of Electors to the Professorship of Applied Mathematics invite applications for this Professorship held in the Department of Applied Mathematics and Theoretical Physics (DAMTP) from
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We are seeking a talented and highly motivated PhD student (m/f/d) to undertake pioneering research in bioinformatics and genomics at the interface with biology. The applicant (m/f/d) should bring
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4 Jun 2024 Job Information Organisation/Company Atominstitut TU Wien Department Atominstitut Research Field Physics » Mathematical physics Researcher Profile First Stage Researcher (R1) Country
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selection criteria You must have completed a Norwegian doctoral degree, or a corresponding foreign degree recognized as equivalent to a Norwegian PhD in Mathematics Education or Educational Sciences
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economy. The Department of Mathematical Sciences at University of Nottingham Ningbo China (UNNC) seeks to fill an academic position at the level of professor. The Department of Mathematical Sciences
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: Possess a PhD degree in computer science, electronic engineering, applied mathematics, perception sciences, etc. Background knowledge in signal/data compression, and data-driven and machine learning