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Field
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As Austria's largest research and technology organisation for applied research, we are dedicated to make substantial contribution to solving the major challenges of our time, climate change and
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Engineering, Physics, Applied Mathematics, or related discipline. Proven track record in numerical methods and computational fluid dynamics. Proven track record in machine-learning methods for computational
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, computer science, software/systems engineering, and data science. Experience with NLP/LLMs and/or requirements engineering is highly desirable; familiarity with model-based systems engineering, safety-critical
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your programme of study: search for the ‘Course Title’ using the programme code: 8060F select ‘Electrical and Electronic Engineering PhD (full time) - 8060F' as the programme of study You will then need
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Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply Please read and complete this document as your Personal statement, and upload
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: MSc in materials science engineering. Backgrounds in chemistry, physics, computer science or a related area are also welcome. Good expertise or strong interest in numerical modeling, machine learning
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impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration. Challenge. Change. Impact! Faculty Mechanical Engineering From chip to ship. From machine
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microelectronics: In this project, you would develop advanced low-power mixed-signal (analog + digital) circuitry on CMOS chips which will drive our custom implants Bionic Vision implantable probes: In this project
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Challenge: Silicon chips do not operate in harsh environments Change: Development of pMOS GaN Technology to complement nMOS GaN Impact: Operate microelectronics in harsh environments Job description
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6 Nov 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Communication engineering Engineering » Electrical engineering Researcher