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theoretical ecology, geosciences, applied mathematics, environmental physics, or a related field. Research experience in numerical modelling, preferably with knowledge of either eco-evolutionary models and/or
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Physics, Chemistry, Applied Mathematics, or related fields. Desirable: Fluent English, spoken and written Strong background in computational Physics and Statistical Physics Previous work experience in
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: 2025/07/13 11:59PM (posted 2025/06/06, listed until 2025/08/25) Position Description: Apply Position Description In the Faculty of Faculty of Computer Science, Electrical Engineering and Mathematics
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, Electrical Engineering and Mathematics at the Department of Mathematics the following position is to be filled as soon as possible Postdoctoral Researcher (f/m/d) (Salary level according to 13 TV-L) with 100
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: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically mathematics, physics). For Postdoc applicants: Excellent track record in computer science
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Research Assistant (m/f/d) in the field of Theoretical Ecology and Evolution or Computational Biolog
of the working group Ability to conduct independent scientific research Excellent proficiency in the field of mathematical modeling Solid knowledge of statistical analysis methods Very good command
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Spectral Theory" at the Mathematical Institute at the Georg-August University of Göttingen. Your profile Master degree in mathematics or equivalent Analytical profile with a research focus in harmonic and
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in full-time studies in the fields of computer science, mathematics, physics, electrical engineering or related courses with good to very good grades Programming experience, especially good to very
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, geophysics, geology or a closely related field Fluent in English (spoken and written) Strong motivation for mathematical inverse methods Strong motivation for team collaboration Experience with paleomagnetic
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equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep learning, or signal processing; familiarity with