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LevelMaster Degree or equivalent Skills/Qualifications Solid background in Machine Learning and Deep Learning. Experience or interest in agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen, or similar
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Assistant/Associate Professor of Practice in Human-AI Interaction, Machine Learning, and Data Design
developing, training, and deploying advanced AI, data, and machine learning systems from a human-centered innovation lens. Preference will be given to candidates whose background includes i) experience
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of relevant research experience. Background conducting quantitative research in healthcare. Technical Skills or Knowledge: Proficiency in optimization, statistics, machine learning, econometrics, or AI
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AI and data science, particularly in dynamic settings where observations are collected sequentially and decisions influence future outcomes. This project will develop novel machine learning and
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the Faculty of Information Technology and Electrical Engineering . Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/308322/phd-candidate-in-empirica… Requirements Research FieldComputer
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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prepared for changes to your work duties after employment. Required selection criteria You must meet the requirements for admission to the Doctoral Programme in Computer Scienc e, see Section 6-1 of the PhD
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, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a specific subject see General syllabus
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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, engineering computation, operational research, management science and applied statistics, FinTech, data science and machine learning. There are currently 56 academic staff and about 154 research personnel in