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Help shape the next generation of aircraft. At TU Delft, you will develop advanced simulation and optimization tools to improve engine-airframe integration, aerodynamic efficiency and noise
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layer for gene expression control and numerous other processes in the cell. In this context, individual and combinatorial modifications guide spatiotemporal recruitment of regulatory factors to specific
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transport modeling and Bayesian inversion techniques. Building on existing modeling frameworks, you will help develop and apply an integrated system that optimizes fire emissions by minimizing discrepancies
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design specific constructs to edit transcription factor genes and their target promoters, and analyse the effects of optimized gene expression regulation on plant performance under optimal and field-like
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expertise, preparing them optimally for future challenges.
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, and actuator design. Your main tasks will include to: Design robotic components and actuators that respond to chemical signals. Optimize geometries and model deformations to match timescales of chemical
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: Develop AI-assisted experimental workflows for oxide semiconductor deposition, aiming to accelerate process optimization and unravel new process–property relationships, and contributing to an EU Horizon
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Making Under Deep Uncertainty; experience using Multi-objective Optimization; experience working with stakeholders on climate adaptation decision-making; experience in river, coastal, or delta systems
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: - A PhD degree in optimization or systems and control theory. - A strong mathematical background and an interest in conducting theoretical research. - A proven track record. - Excellent English
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. Helpful criteria: experience with Dynamic Adaptive Pathways Planning or other methods from Decision Making Under Deep Uncertainty; experience using Multi-objective Optimization; experience working with