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Field
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suitable wireless link at any moment. In this PhD project, you will develop novel concepts for intelligent hybrid RF–OWC networks that optimize wireless service delivery in real time. Research topics include
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fluorescence microscope optimized for imaging individual cells within microtumors. Through this work, the PhD candidate will receive hands-on training in the design, implementation, and optimization of a state
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-MID prototyping and performance optimization of structure-embedded sensors and nanogenerators. Depending on applicant’s skillset the research objectives may include implementation of AI-assisted in
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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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optimization of machine learning methods for processing Quantum OCT (Q-OCT) signals. Design, training, and testing of neural network architectures for artefact and dispersion removal in Fd-Q-OCT and SS-Q-OCT
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capable of predicting optimal PISA formulations and significantly reducing experimental screening efforts. The successful candidate will receive multidisciplinary training spanning polymer chemistry
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PhD thesis student (f/m) at ESRF and University of Bath to study CO₂ capture by coupling X-ray Raman
critical electronic changes governing CO₂ capture under realistic conditions, providing the essential scientific insights needed to design more efficient, durable, and optimized materials for fighting
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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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crack initiation and propagation; Development and validation of a digital twin with an appropriate level of maturity; Proposal and evaluation of new cluster architectures; Validation of optimized
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PhD Position Simulating the Airspace of the Future: Fleet & Network Optimization for Future Aircraft
current and future aircraft models + Evaluating how these differences affect fleet assignment and network planning + Optimizing airline operations (e.g., fleet composition, scheduling, routing) based on new