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Optimization: Mathematical Phylogenetics During this project, you will work on fundamental graph-theoretic and algorithmic problems in mathematical phylogenetics. Job description The Discrete Mathematics and
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implants using finite element analysis and topology optimization. Join us to shape the future of personalized orthopedics Job description Faculty of Mechanical Engineering at TU Delft Are you passionate
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candidate to join our team and work on this exciting project. The PhD project will encompass theoretical and numerical modelling, necessary to simulate and optimise the effect of surface modifications
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networks also need to evolve, offering, e.g., ubiquitous connectivity and decentralised data-center capabilities to optimize urban performance. This project aims to explore how telecommunications networks
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, patient motion, and more. Today, these parameters are either manually configured, heuristically optimized, or compensated post hoc using multi-level calibration scans or corrections, which introduces
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this project, you will set up high resolution, realistic numerical simulations of Greenland fjords, and study the ocean dynamics and the interaction with ice. This project is a collaboration between the TU Delft
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software engineering skills in Python. Strong background and research experience in astrodynamics/orbit determination and numerical methods. Experience in usage of PRIDE data is a strong plus. Experience in
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architecture, preferably with a focus on structures. Know the basics of (structural) glass and of Dutch masonry (heritage) buildings. Have a solid understanding of computational/numerical modelling and
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OCT system must be optimized in terms of noise and detection efficiency. You will do this based on experiments and physical modeling of SC, detector, and system performance. Second, the OCT system must
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, architectural engineering, (applied) physics, applied mathematics, or a related field is required. Strong mathematical and analytical skills are essential. Solid understanding of numerical modeling and signal