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disciplines (electronics, electrical engineering, mechanics, biology, etc.). In particular, expertise has been developed in the design of systems obtained by interconnecting subsystems, for which
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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24th April 2026 Languages English English English The Department of Electronic Systems has a vacancy for a PhD Candidate in Distributed Machine Learning Apply for this job See advertisement This is
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such interdependencies explicit while remaining compatible with established workflows. The aim is to propose a structured representation of vessel designs that (1) integrates with current design practices and tools, (2
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Technologies de l'Information et de la Communication Field: Telecommunications / Machine Learning / Statistical Signal Processing. Research Lab: L2S (Laboratoire des Signaux et Systèmes) Advisor: Antoine BERTHET
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, confirmation from previous academic institution, etc.). Application deadline For current information, please visit: https://qbm.genzentrum.lmu.de/application/ Submit application to https://qbm.genzentrum.lmu.de
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of full-time. Your qualifications You have graduated at Master’s level in biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered
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engineering Engineering » Computer engineering Engineering » Electrical engineering Engineering » Other Mathematics » Applied mathematics Researcher Profile First Stage Researcher (R1) Application Deadline 22
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details, the following tasks will be carried out in parallel: 1. The PhD student will extend the current database (see, J. Chem. Theory Comput.2025, 21, 8010−8033) by obtaining highly-accurate reference