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/363551/phd-physics-informed-machine-le… Requirements Additional Information Website for additional job details https://www.academictransfer.com/363551/ Work Location(s) Number of offers available1Company
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4 Sep 2026 Job Information Organisation/Company Grenoble INP - Institute of Engineering Department Engineering Research Field Engineering » Computer engineering Researcher Profile Other Profession
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friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a PhD
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machine-learning and AI methods for complex engineering and industrial systems, with a particular focus on improving their reliability, availability, and operational performance while enabling more
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in weekly meetings and help to prepare reports and presentations for project sponsors. Minimum Qualifications: Requirements include a PhD in Engineering or a closely related field. Experience managing
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3 Year, full-time PhD studentship Eligibility: Open to home, EU and international students Bursary p.a: £21,805 University fees and bench fees: This studentship will cover university fees
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11th October 2026 Languages English English English Faculty of Science and Technology PhD Fellow in Remote Sensing of Rain-On-Snow Preconditioning Sea Ice Melt Onset Apply for this job See
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teaching and supervision of bachelor's and master's students in areas related to your expertise. Your competencies We expect you to have: A PhD in electrical engineering, energy engineering, mechanical
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across the following areas: A PhD in Civil, Mechanical, Mechatronic, or a closely related engineering discipline. Demonstrated hands-on engineering skills with a track record of physical prototyping
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to teaching, research, industry engagement and academic leadership in areas including communication engineering, network engineering, network security, telecommunications infrastructure, wireless and space