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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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theories and numerical methods, carrying out and analysing field and remote sensing observations and conducting and analysing numerical model simulations. The PhD position is funded by the German Research
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) software for topology-informed biomedical image analysis and large foundation models. You will be responsible for Develop new machine learning algorithms for microscopy image analysis problems (2D/3D/4D/5D
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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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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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of Munich, Cologne and Hanover as well as the German Weather Service in Offenbach and Lindenberg. The partners combine leading expertise in modeling and observing clouds and their radiative properties with
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modelling, starting as soon as possible. The position is funded for 36 months. Remuneration is in accordance with the German public tariff scheme (TV-L Brandenburg), salary group E 13. This is a part-time
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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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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
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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