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5 Jan 2026 Job Information Organisation/Company Department of Evolutionary Population Genetics Research Field Biological sciences Researcher Profile First Stage Researcher (R1) Country Germany
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team founded in 2019. About the Department: The Department of Biological Sciences offers two Ph.D. tracks (Bioscience and Ecology and Evolutionary Biology) and has over 100 graduate students and over
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Deadline 15 Jan 2026 - 23:59 (UTC) Type of Contract To be defined Job Status Full-time Offer Starting Date 15 Feb 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Academic context and supervision
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Max Planck Institute of Animal Behavior, Radolfzell / Constance | Radolfzell am Bodensee, Baden W rttemberg | Germany | 15 days ago
ecology, evolutionary biology, molecular biology, quantitative behavior, computer vision, and physics of behavior. We envision this project to primarily involve laboratory-based investigations, although
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video annotation). Training and supervision will be provided by Daniela Santos Nunes, who uses fly genital morphology as a model for evolutionary change, Sebastian Kittelmann, an expert in the use
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Max Planck Institute for Biology Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 18 days ago
, and evolutionary biology. We invest in the next generation of scientists who will gain expertise and skills to study complex biological processes that bridge the gap between molecules and living
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simulate hydrodynamic and pollutant transport processes, their computational cost limits their suitability for real-time emergency decision-making. This project addresses this challenge by combining physics
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pressures from climate change, urbanisation and ageing infrastructure. Although high-fidelity numerical models can simulate hydrodynamic and pollutant transport processes, their computational cost limits
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an emphasis on the development of methodologies and techniques for Evolutionary Computation and Machine Learning. Work plan: Review of the state of the art in Machine Learning and Deep Reinforcement Learning