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executing the experiments Developing relevant algorithms for experimental data post-processing Mentor and work closely with multiple Ph.D. and M.S. students as well as four principal investigators from
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 9 days ago
physical and MAC layers and the proofs of concept for the practical assessment of the performance of selected algorithms. The position will be based at Inria Saclay, with expected collaboration with other
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Collaboration. The primary focus of this post will be the development of computational pipelines for the automated extraction and discovery of image-derived phenotypes (IDPs) across multiple imaging modalities
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning for improving
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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systematic validation and performance assessment. At ING, large document flows and multiple RAG-based initiatives call for robust mechanisms to evaluate model outputs. You will work with ING Analytics
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discoveries in gene regulation, immune variation, disease mechanisms, and functional cell states. Lead analyses that directly enable first-author publications, with multiple manuscripts already under review
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convenient to be determined by both parties). The positions are fully funded for multiple years with a recent award from the National Institutes of Health on Developing Novel Technologies That Ensure Privacy
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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various processes in modern machine learning, including learning, inference, and generation. In particular, we are working to establish novel theories and algorithms that enhance the efficiency