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Field
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, and unmodeled dynamics remains a key challenge. This position focuses on developing and validating methods that jointly address safety, performance, and reliability of learning-based control and
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partners in the digital health and health delivery ecosystem. Research Responsibilities Responsibilities will vary depending on the Fellow’s background, but may include: • Developing machine learning
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century. Join the Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB ) – of the University of Bordeaux! This mixed research unit develops research themes in the field of MRI methodology and
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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uncertainty quantification. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and
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lasers with high-average and high-peak power Building of optical cavities Running existing simulation codes in Julia and processing their results. Helping to develop new models and algorithms to simulate
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interpreting large-scale spatial transcriptomic data from multiple clinical trial. You will collaborate with an interdisciplinary teams of scientists and clinicians to develop bioinformatics pipelines and tools
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of privacy-preserving artificial intelligence for the benefit of humanity. What You Will Do: Research (Federated Continual Learning): You will develop novel and privacy-preserving algorithms that allow
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data for model calibration and validation. Apply sensitivity analysis and optimization algorithms to refine model parameters and improve predictive accuracy. Contribute to code development, documentation
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of teaching and learning. Successful candidate will bridge the fields of AI development and education research, working closely with other AI researchers in M3S to contribute in both the creation of generative