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machine learning, distributed systems, and blockchain technologies. Your immediate leader will be the Head of the Cryptology Unit at the Department of Information Security and Communication Technology. The
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-principles electronic structure calculations Perform materials screening including machine learning to identify promising thermoelectric materials for cooling technology The successful candidate is expected
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machine-learning methods to enhance predictive capability and enable adaptive process control. Experimental work will include laboratory- and industrial-scale forming trials, supported by comprehensive
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Knowledge about energy systems, especially the operational characteristics of renewable energy production (wind/solar) and batteries Knowledge and interest in applying AI/machine learning to time-series data
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energy applications. You must have experience with data analysis, machine learning, or AI-supported methods applied to engineering or safety problems. PLEASE NOTE: For detailed information about what the
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, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier. Duties of the position Complete your doctoral education leading
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, you can expect: An attractive and supporting learning environment Participation in research groups Close supervision Skilled supervisors Excellent job prospects The programme is administered by
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Innovation, SFI-CELECT (Research Centre for Effective Engineering and Learning in Complex Systems) . The positions are 3-year doctoral research fellowships starting in 2026. The PhD candidates will be embedded
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for admission are: TOEFL – a total score of 575 points for the written test or 233 for the computer-based version or 90 points on the internet based test IELTS – a score of 6.5 Exemptions are made for applicants
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career plan will be prepared that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. Research topic The Research