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trophoblast cells in a small animal model. The project is part of the new Collaborative Research Center (SFB 1713) “Maternal Immune Activation: Causes and Consequences”. We are seeking a highly motivated and
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analysis problems, especially tracking the motion of objects, which are driven by real applications in life science research Developing solutions to integrate large foundation models into microscopy image
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viability using multiple detection techniques (FACS, microscope, spectrophotometer). Collaboration on the analysis of created bacteria in Zebrafish models. Analyse data, contribute to scientific publications
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contributes to the improvement of climate prediction models. The Atmospheric Chemistry and Atmospheric Microphysics departments are looking for a committed doctoral student to carry out this project. You can
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approaches across a range of model organisms to understand how and why we age. As a PhD candidate at FLI, you’ll be part of an international and interdisciplinary environment where basic science meets
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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experience growing, managing, and phenotyping plants in the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand
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combines microbial genomics, transcriptomics, and in vitro infection models to explore the adaptive trade-offs between drug resistance and virulence phenotypes. The position is funded for 3 years and
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student (m/f/d) to conduct research on a DFG-funded project focused on trace fossils, and the evolution of behavioral complexity over the Ediacaran-Cambrian boundary. This project will combine detailed
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data Research experience with various demographic models (e.g. msprime, ABC or RELATE) Research experience in the denovo assembly and scaffolding of high-quality genomes using PacBio and Hi-C data