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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 120 nationalities, 14 000 students, 400 professors and close to 5000 faculty and staff working on our dynamic
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Responsibilities: Ensure communication with internal and external stakeholders Organize and prepare content/analysis for project events, such as stakeholder meetings and policy briefs Network with researchers and
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? With data-driven methods, new opportunities arise to understand ecosystems as complex, dynamic networks. This project aims to analyse the world’s most extensive eDNA database, consisting of weekly
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a focus on mentoring and individual career development. Training in state-of-the-art technologies and data analysis as well as research management, oral and written communication, and networking
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metabolism in rare and more common neurodegenerative or neurometabolic diseases. We exploit genomic and post-genomic data to fill gaps in metabolic networks, discover new enzyme functions, and elucidate
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that you develop. Both in the practical and simulation work you will be guided and supported by other post-docs and senior researchers, in Luxembourg and from our international network of collaborators. You
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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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products is a strong plus. Excellent laboratory and organizational skills; ability to work independently and as part of a collaborative team. Good communication skills in English. In
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methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing
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, B., Holtkamp, E., et al. Integration of variant annotations using deep set networks boosts rare variant association testing. Nature Genetics (2024) Marconato, L. , Palla, G. , Yamauchi, K. A