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following areas: Machine Learning, Deep Learning, Reinforcement Learning, Data Mining; Programming; Parallel programming and High-Performance; Computing; Scientific computing, Numerical methods, and Numerical
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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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develop an AI-enhanced Human-Machine Interface (HMI) that enables a more intuitive and adaptive use of the system in home settings. The goal is to create a supportive solution that can adapt to changing
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to contribute to high quality, large-scale undergraduate education. Job description As Lecturer, your responsibilities will be centered around teaching and education. You will: Teach quantitative courses in Year
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(adaptive) imaging strategies and reconstruction. The research combines ultrasound physics, signal processing, machine learning, computational imaging, and clinical translation. Beyond your individual
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adaptive resource allocation, AI-driven network orchestration, dynamic beam steering, joint communication and sensing, and cross-layer optimization. Machine learning techniques will be investigated
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an enthusiastic and highly motivated researcher. You have, or will shortly, acquire a PhD degree in the field of Human-Computer Interaction, Interaction Design or Interaction Technology or equivalent Ideally, you
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interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362788/post-doc-learning-interactions-… Requirements Specific Requirements PhD Degree in Physics Preferably
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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
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23 Jul 2026 Job Information Organisation/Company University of Twente (UT) Research Field Educational sciences » Education Educational sciences » Learning studies Researcher Profile First Stage