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10 Apr 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Control engineering Researcher Profile
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of high‑tech system design—such as the design of lithography machines—can already be automated, current design‑automation tools remain limited to specific domains or subsystems. Given the growing complexity
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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Automation, Cybernetics, Mathematics, Electric Energy, Industrial Economics, Data Science or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been
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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
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-driven methods to improve the reliability of monitoring systems used for energy efficiency and resource optimization. Your profile Master's degree in Electrical Engineering, Industrial Engineering
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FieldTechnology » Computer technologyEducation LevelMaster Degree or equivalent Skills/Qualifications Must hold a Master’s in Electrical Engineering, Computer Science or Computer Engineering. General computer
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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growth methodology based on real-time growth monitoring enabled by advanced in situ characterization tools (RHEED, ellipsometry, curvature measurements, flux monitoring), coupled with machine-learning (ML
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channel. This will be followed by designing a new resilient waveform for UOWC and developing a computer-based simulation to evaluate its performance. Finally, the study will use existing UOWC channel