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technologies (SiC and GaN), advanced and intelligent control, artificial intelligence and machine learning for power electronics, digital twins, condition monitoring and predictive maintenance. Important
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at approaching these limits. Main areas of interest are free space optical communications, fiber communications, source coding, channel coding, (multi-user) information theory, security, and machine learning. You
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-bandgap semiconductor technologies (SiC and GaN), advanced and intelligent control, artificial intelligence and machine learning for power electronics, digital twins, condition monitoring and predictive
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international levels, you will contribute to interdisciplinary collaboration, academic networks, and the co-supervision of PhD candidates.In education, responsibilities include teaching and, over time
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learning, machine learning, AI, and specialized computer vision courses, as well as support curriculum development, academic leadership, and mentoring within the department. You will supervise PhD candidates
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resources engineeringEducation LevelMaster Degree or equivalent Skills/Qualifications Experience with hydraulic modelling, optimisation libraries, uncertainty quantification, data science, machine learning
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Listen Published Thursday 10 Sep 2026 Deadline Wednesday 30 Sep 2026 Work area PhD Organisational unit Erasmus School of Health Policy & Management (ESHPM) Salary € 3.204 - € 4.051 Employment 1 fte
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adaptation, synthetic data generation, and cross-modal learning to enable models that generalize across defect types and machine configurations. This ensures scalable, accurate defect detection even in low
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are free space optical communications, fiber communications, source coding, channel coding, (multi-user) information theory, security, and machine learning. You will have the opportunity to work with and in
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, ontology engineering, formal logic, knowledge graphs, data annotation, user interaction, cognitive modelling; Knowledge of, or interest in, agentic AI, NLP, HPC, LLMs, machine learning; Strong programming