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that embryos typically develop healthy organs, even though in nature they are frequently exposed to genetic and environmental stressors. The Rocha Lab subjects developing tissues to diverse stressors, including
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication
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-responsive proteins to develop genetic switches and circuits in therapeutically relevant bacteria. Your tasks: Use computational tools to design protein structures with desired properties Produce
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on the influence of Alzheimer’s disease and aging on changes in cognitive functions in humans. The project combines cutting-edge technologies from genetics, proteomics and statistical modeling to understand
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advanced wet-lab experience in molecu-lar biology and in reverse genetic approaches. You fit to us: • You are an outstanding and highly-motivated postdoc-toral researcher with the ambition and commitment
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Immunology and Computational Biology Reference number: 2025-0105 We are deploying advanced in vitro and in vivo model systems, genetic perturbations and single cell technologies with spatial readouts to study
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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integration. Role: Apply ML to barley genomic data, emphasizing gene regulation and genetic variation Collaborate with geneticists, breeders, and industry partners to move research toward applications Explore
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Postdoc position: mechanisms of autoimmunity & autoinflammation in inborn errors of immunity (m/f/d)
to decipher key regulators of human immune homeostasis (Ardy RC et al., Gastroenterology 2018; Wang L et al., Nat Genet 2021; Salzer E et al., Science Immunol 2020; Block et al., New Engl J Med 2023