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development fund of the department, IT Academy and a recently started project “Smarter use of data via machine learning” and has close ties to the Estonian Centre of Excellence in Artificial Intelligence (EXAI
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artificial intelligence (AI) and big data mining methods for real-time defect detection and adaptive process optimization in Electron Beam Powder Bed Fusion (EB-PBF) of refractory metals such as tungsten and
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management information systems, business analytics, supply chain and artificial intelligence. Qualifications: Ideal candidates will have a Master’s degree in the discipline for teaching at the undergraduate
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/Qualifications Experience in: - Development of artificial intelligent algorithms. - Explanaible artificial intelligence - LLM experience - Virtual intelligence entities using reinforced learning
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will be considered on a case-by-case basis. The scholarship is funded by G-Research. Research focus The PhD topic must focus on Artificial Intelligence (AI) in relation to the research areas of one
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artificial intelligence (AI) researchers. Publish findings in high-impact journals and present at international conferences. Expected Outcomes: A partially explainable AI model for context-aware NIBP
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modeling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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fields. A PhD degree in Artificial Intelligence, Informatics, Computer Science or related fields is preferred to teach at the graduate level. The ideal candidate will possess a minimum of twoyears of
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enterprises (SMEs) with artificial intelligence (AI) and data science technologies through knowledge transfer and sprint projects. The Hub’s core programmes are funded by the Science and Technology Facilities
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community like ours. Furthermore, we are looking to welcome a colleague who fosters collaboration at all levels. Our ideal candidate has: A PhD degree in Artificial Intelligence, Computer Science, Data