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Field
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cardiovascular medicine. Mechanical Circulatory Support (MCS) technologies offer life-saving potential, yet optimal patient selection, timing, and device strategies require deeper mechanistic and clinical insight
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research • Deep learning and predictive modeling • Natural language processing and large language models for biomedical data • Drug response prediction and treatment optimization • Biomedical knowledge
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Utrecht, CWI, Dutch municipalities, DSOs, and other societal/industry partners. The project brings together expertise in energy informatics, optimization, data science, social sciences, and governance
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retrieve shapes, overlay errors, and other geometrical parameters of the target using methods ranging from local and global optimizers to priors and neural networks developed by partners in the project. Job
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and prior knowledge of the sample geometry. You investigate and optimize the trade-off between accuracy and imaging speed. For real-time application, the speed and accuracy of the algorithms will be
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Computational de novo design of VHH and scFv binders to blood coagulation factors such as factor Xa and prothrombin. Wet lab production and screening of the aforementioned binders. Optimization
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systems, optimizing audio playback levels, and supporting other acoustic interventions to improve occupant comfort and building performance. The research will adopt a human-centered approach, placing
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at cryogenic conditions: Many advanced technologies — like quantum computers, powerful microscopes, and chip-making tools — require extreme cooling. However, the optimal design of cooling systems at cryogenic
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during inspiration/expiration (b) stratification of patients to identify sub-groups that would benefit most from different HFNC modalities, and (c) optimization of flow rates to individual patient
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replication, pathogenesis, and host-fungi interactions to inform rational drug design and optimization of antifungal therapeutics. Collaboration and Project Management: Coordinate with multidisciplinary teams