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models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance multimodal deep learning models combining CT imaging and clinical data, trained on the unique
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profitability. Examples include optimizing production speeds to balance output, equipment deterioration, and energy consumption in manufacturing, or designing dynamic pricing and allocation policies in rental
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, rental platforms, and production systems—where decision-making must balance conflicting objectives, leverage real-time data, and ultimately support sustainable profitability. Examples include optimizing
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life-long follow-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance
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-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance multimodal deep learning
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developing morphing surfaces enabled by Shape Memory Alloys (SMAs). These adaptive winglets are designed to optimize aerodynamic performance by responding to temperature variations and incorporating active
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light/heating modules, and selection and sorting routines. Guided by machine learning, we will perform directed evolution experiments where we optimize the synthetic genome that encodes for a biological
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, which integrates healthcare, research and education on pediatric cancer, in a single location in Utrecht. Our institute aims to provide the highest level of care for all children with cancer, with optimal
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optimize the synthetic genome that encodes for a biological function such as shape manipulation. Next to all this, the candidate will also do research on entropic segregation of synthetic genomes by testing
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for: design and optimize bioprocesses for cultivated meat production, including media formulation, cell growth, differentiation, and harvesting techniques; conduct and optimize the production of porcine and