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on methodology and academic writing Other career-promoting work Required selection criteria A doctoral degree (PhD) in solid mechanics, computational mechanics, or a closely related field, with a strong academic
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There is a vacancy for a PhD Research Fellow in Arctic Paleoceanography at the Department of Earth Science and the Bjerknes Centre for Climate Research . The position is for a fixed-term period of 3 years
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mechanisms in early embryonic development, leveraging our state-of-the-art epigenetic and epitranscriptomic methodologies (Nature, 2016; Nature Genetics, 2020; Nature Structural & Molecular Biology, 2023
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fluid mechanics from the same project can be found here . About the project/work tasks Prof. Dr. Yan Li ’s research group seeks a highly motivated and exceptionally talented PhD research fellow in
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
in theoretical modelling, preferably within active matter physics Solid programming skills Desired qualifications: Experience in statistical physics, solid mechanics, or fluid mechanics Experience with
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
programming skills Desired qualifications: Experience in statistical physics, solid mechanics, or fluid mechanics Experience with data-driven modeling, parameter estimation, or model calibration Familiarity
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/Anders Lien 10th April 2026 Languages English English English PhD Research Fellowship in Quantitative Imaging and Cell Mechanics of Early Embryo Development Apply for this job See advertisement About the
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will be given also from members of the Earth Surface Science research group that work mainly in the physical geography domain, focusing on investigating causes, mechanisms and impacts of different
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discovered self-correction mechanisms. The project ultimately aims to provide blueprints for a plasma-accelerator demonstrator facility for groundbreaking experiments in strong-field QED. In particular
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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova