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                . We are taking part to a Marie Skłodowska-Curie Doctoral Network project “Advancing Energy Conversion Technologies: High-Frequency Magnetics in Modern Power Electronics” (MAGNIFY). The project is a 
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                31 Oct 2025 Job Information Organisation/Company University of Twente (UT) Research Field Physics » Electronics Physics » Quantum mechanics Researcher Profile First Stage Researcher (R1) Country 
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                Vacancies PhD position on physics of tunnelling devices for ultralow-power electronics Key takeaways The integrated devices & systems (IDS) and power electronics (PE) group at the University 
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                Research Studentship in Engineering 3.5-year D.Phil. studentship Project: Electronic-free Mechanical Oscillators for Fast Locomotion in Soft Robots Supervisors: Prof Antonio Elia Forte Soft robots 
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                interested, please send your complete application via email to dss at in.tum.de . As an equal opportunity employer, TUM explicitly encourages applications from women and all others who would bring additional 
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                27 Oct 2025 Job Information Organisation/Company Grenoble INP - Institute of Engineering Department Engineering Research Field Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country France Application Deadline 2 Nov 2025 - 20:00 (Europe/Paris) Type of... 
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                The Innovative Electron Microscopy Department develops and applies electron microscopy methodologies for nanoscale and atomic-resolution characterization of soft functional materials and their 
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                : Apply Position Description PhD student in Physics of Superconducting Electronics The Department of Physics is located in the AlbaNova University Center and has approximately 240 employees, 250 students 
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                related to staff position within a Research Infrastructure? No Offer Description Description The Electron Microscopy of Materials (EMM) unit at Linköping University invites applications for a PhD position 
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                develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven