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research project “Is the brain network involved in sentence comprehension replicable and robust?”, led by Dr. Jurriaan Witteman. The project will investigate the neural mechanisms underlying sentence-level
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assessed by means of a high-fidelity end-to-end simulator. The current design of the NGGM DFAOCS could benefit from the latest advances in control theory and the use of a robust control framework in which
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to imagine novel task configurations and learn robust manipulation policies from just a few real demonstrations. You will work at the intersection of 3D computer vision, physical simulation, and robot learning
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and analysis pipelines are underway. Working closely with the principal investigator and collaborators, you will complete the main analyses, stress-test robustness, and contribute to the writing
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pipelines, multi-modal knowledge graphs, and training-ready datasets with robust provenance and validation. Track B — GPU-Accelerated Scientific Foundation Models You will design and train large-scale multi
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security-oriented workflows. This includes designing methodologies that ensure traceability, robustness and bias mitigation in AI models, as well as creating prototype tools that demonstrate how transparent
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, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network
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, the leader aims to build a robust network that mitigates failures caused by the follower’s actions. A key characteristic of such applications is the presence of symmetries. For instance, a symmetric network
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are developing technology to robotically manufacture robust optical circuits for quantum technology and beyond. We provided the circuit boards for the AQuRA optical lattice clock and are offering
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development, clinical guidelines and shared decision-making between healthcare professionals and patients. . However, robust and standardised methods to consistently quantify this impact across entire care