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extension for another 6 months. It is based in the Schulenburg group (https://evoecogen-kiel.de/ ). The PhD project aims at understanding how evolutionary principles can be harnessed to constrain bacterial
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who works at the intersection of numerical methods, scientific computing, and data-driven modeling. The position is devoted to the development, analysis, and implementation of flexible, tailored, and
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hours per week, initially limited until 31.12.2028 Remuneration according to TV-L The Göttingen Campus is hosting numerous prestigious and internationally renowned research institutions. This includes
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 2 months ago
. Numerical methods, in particular FEM-based stress analysis at initiation sites within the framework of local fracture approaches, provide a natural bridge between experiment and mechanistic understanding
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coastal sediments and their role in polar biogeochemical processes. Your main responsibilities will include: Sampling and geochemical analysis of Antarctic sediment samples Incubation experiments and stable
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(meta-)genomes Experience in the computer-assisted analysis of large biological datasets (e.g., using R, Python, and Bash/Linux environments) Very good written and spoken English skills Ability to work
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mathematics, computational physics, or a related discipline (PhD is advantageous) Experience with numerical modelling and analysis of large simulation datasets Knowledge of physical oceanography and experience
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8 Jul 2026 Job Information Organisation/Company Saarland University Department Data Driven Simulation and Analysis in Material Science Research Field Computer science Researcher Profile Established
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, climate science, physics, mathematics, or a related field (PhD is advantageous) Experience with numerical modelling and analysis of large simulation datasets Knowledge of ocean biogeochemistry or Earth
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: Degree in computer science, computational science, applied mathematics, or a related field Experience with numerical modelling and analysis and handling of large simulation datasets Strong knowledge of HPC