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professor, one assistant professor, one postdoc, and a large number of PhD students. The project includes strong partnerships with the University of Leipzig (Bioinformatics, Prof. Peter Stadler
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desired. Knowledge on statistical methods and their application is an extra merit. Good knowledge in GIS and R is a merit. Proven excellence in written and spoken English is essential. The fieldwork will
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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charges Thermochronometry and rock surface dating You will be part of the dynamic and interdisciplinary LUMIN team, which includes engineers, scientists, postdocs, and PhD students working collaboratively
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experience with spatial data analysis using GIS tools or spatial libraries and familiarity with common land-use datasets would be advantageous familiarity with environmental or agricultural economics research
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a small multicultural research group with PhD students and postdocs of different nationalities. Thus, the group’s communication is in English. We aim to analyze the metabolic homeostasis
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ecology, and/or restoration ecology. Experience in design, execution and analysis of acoustic data is desired. Knowledge on statistical methods and their application is an extra merit. Good knowledge in GIS
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characterization of glycoside hydrolases, and a postdoc working on computational modelling of the same enzymes. The PhD focuses on ligand-observed NMR analyses and other relevant methods to provide insight
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knowledge in plant species identification. The successful candidate should be able to independently conduct statistical analyses in R and hold a valid driver's license. Experience in GIS and handling large
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of responsible human-AI collaboration. The successful candidate will become a member of the Multi-Agent Systems Group, Artificial Intelligence Department and will work under the supervision of Dr. Jakob Schoeffer