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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
1st October 2026 Languages English English English The Department of Mechanical and Industrial Engineering has a vacancy for a PhD Candidate to conduct research on Artificial Intelligence
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We are looking for a PhD-candidate in a unique project investigating the subsurface heterogeneity and geohydrological conditions below dikes, focusing on the risk of backward erosion (piping). Your
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RAS can be used for the inspection, maintenance and repair of new infrastructure in renewables (wind, solar, geothermal, tidal, hydrogen) and nuclear (fission and fusion), and to support the
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effectiveness. Overcoming these barriers is a key target of this CDT. The CDT’s research projects will focus on how RAS can be used for the inspection, maintenance and repair of new infrastructure in renewables
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reduced maintenance demands which are key for the broader adoption of offshore wind energy. However, several challenges must be addressed, such as the machine's relatively low power density and power factor
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decade. This PhD project places you at the forefront of this challenge, developing the tools and insight needed to design the next generation of offshore aquaculture infrastructure. Research Overview
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04.08.2026, Academic staff Fully funded PhD position (TV-L E13) at the Technical University of Munich (TUM) in Generative AI for Automotive Software Engineering. The project focuses on LLMs, VLMs
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reliably assess fatigue damage and predict remaining lifetime, enabling proactive maintenance strategies that extend service life and reduce CO2 emissions. Through this PhD scholarship, you will contribute
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) Positions PhD Positions Application Deadline 21 Sep 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Oct 2026 Is the job
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% of the UK’s electricity and are central to achieving net-zero targets and ensuring the resilience of national grid infrastructure. Preventive maintenance enabled by condition monitoring systems (CMSs) plays a