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an independent, proactive thinker who thrives in interdisciplinary collaboration, you are excited to contribute new insight into this understudied but ecologically highly relevant research field. Your
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, as well as governance challenges and barriers for achieving healthy coastal environments will be identified. Within this project, the PhD student will be involved in collaboration with stakeholders in
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embedded in the multidisciplinary Bioelectronics research team at TU Delft and collaborate with researchers working on organic bioelectronics, neural interfaces, conducting polymers, microfabrication and
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to the development of new theoretical understanding of sediment-rich estuarine systems and will collaborate closely with other PhD candidates and postdoctoral researchers within the iMose project. Strong interactions
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, relating to craniofacial identification research and machine learning. You will require a computer science background. You will be applying AI and/or machine learning to Face Lab processes in relation
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, Retrieval-Augmented Generation (RAG), agentic AI, software-defined vehicles, and AI-supported software engineering in collaboration with academic and industrial partners. Requirements A completed master's
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high-density 3D Multi-Electrode Arrays (3D-MEAs) — done in close collaboration with experts, providing full support as you learn to analyze this data. o Multi-Omic Profiling: Performing and analyzing
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25th September 2026 Languages English English English The Department of Marine Technology has a vacancy for a PhD Candidate in Deep Learning Enhanced FSI analysis of Modular Floating Structures PhD
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collaboration with the Danish Cancer Institute in Copenhagen, and you will have the opportunity to undertake a research stay in Copenhagen. You will be part of a cross-disciplinary team of cell biologists and
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machine learning. We further appreciate willingness to travel, teach and mentor, collaborate and communicate science. To succeed in this role, you should have: A Master’s degree (or equivalent*) in