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team within the University of Luxembourg aims at: Driving the National Competence Centre activities in Luxembourg to facilitate High-Performance Computing uptake Providing tailored HPC-related training
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→ cell → patient Integrate multi-modal data (genomics, transcriptomics, biosensors, EHR) Perform single-cell and spatial multi-omics analyses at scale Lead high-impact publications and contribute
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) perform in-silico interventions (e.g., gene knock-outs) that create testable hypotheses that will guide future wet-lab experiments. Your mission Lead the development of mechanistic machine learning models
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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hand. You join a project that is scientifically ready to advance into high-impact structural experiments from day one. Ready for you: cHR overexpression and purification: Reproduced in Kraków, full SDS
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computational algorithm(s), perform data analysis, collaborate with biologists and physicians. He or she will lead multiple projects, work in a multidisciplinary environment and present/publish the results in
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QGG - Aarhus University seeks a postdoc researcher in sustainable breeding: developing simulation...
more than 20 countries. We perform basic and applied research within plants, livestock and human quantitative genetics. Our focus areas include quantitative genetics, breeding plans, artificial intelligence
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
pests, or high-throughput phenotyping Solid background in mathematics and scientific programming (R, Python, etc.) along with effective logical reasoning skills Experience with high-performance computing
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with high-performance computing environments. Independent, creative, and able to thrive in a collaborative, interdisciplinary setting. What We Offer A stimulating research environment at Helmholtz Munich
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. In addition, CVI2 provides high-performance GPU computing resources that support the design and training of advanced AI models. The research agenda of CVI2 focuses on cutting-edge topics such as 3D