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Postdoc in "Navigating uncertainty: Planning marine protected areas in a changing Southern Ocean"...
conditions are particularly vulnerable, as their habitats with optimal environmental conditions become increasingly scarce. All in all, these ongoing changes highlight the urgent need to rethink the management
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on the recently published DeepRVAT framework, which leverages advances in machine learning to learn an optimal rare variant aggregation function in a data-driven manner. You will have the opportunity to spend
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exchange and interaction state of the art computing infrastructure (HPC) salary assigned according to the pay scale UKF standard social benefits, e.g. UKF job ticket UKF Your tasks: develop and optimize
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human patient samples and cutting-edge AI-driven analyses Validate computational findings through functional laboratory experiments Develop and optimize protocols involving omics methods, immune cell
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spectroscopic or microscopic methods and subsequent optimization Advancements of experiments, measuring methods and measuring technology and improvement of experimental equipment Presentation of results
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of fluid dynamic modeling and the analysis of thermomechanical stresses, you will accompany the entire development process – from the optimization of electrochemical performance to the elaboration
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Broadband UV-generation position Push the frontiers of nonlinear optics in multi-pass cells Optimize third harmonic generation in nonlinear gases Develop scaling concepts to kJ pulse energy levels General
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
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improved patient outcomes Integration of findings into translational research, collaborating closely with clinicians, imaging specialists, and bioinformaticians to optimize interventional oncology treatments
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decisions and functional consequences in neurodevelopmental disorders and brain cancer. Your Role: Develop and optimize human organoid and assembloid models for studying neurodevelopmental disorders and brain