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Professor of Artificial Intelligence for Multimodal Data Identification number: I-IMI-2025-003574 Application time: 01/29/2026 Hearing: 03/23/2026 For further job related details see link below: Tenure Track
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the Undergraduate Program in Artificial Intelligence in Medicine (UPAIM). Contract type: Full-time Job Description Taipei Medical University is looking for a motivated member with Ph.D. degree with outstanding
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technology using a combination of advanced in situ assay methods, tissue imaging, image analysis, and artificial intelligence. The deep phenotyping group aims to increase our understanding of the tumour
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, FOR ADMISSION TO THE PhD COURSE IN INDUSTRIAL AND INFORMATION ENGINEERING AND ECONOMICS – FOR no. 2 POSITION WITH SCHOLARSHIP: - 1 grant aimed at carrying out research concerning: “Artificial Intelligence (AI
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, rehabilitation medicine, bioinformatics, epidemiology, biostatistics, big data analytics or artificial intelligence analytics A good command of written and spoken English Strong communication skills and a
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may come from: (a) data science, artificial intelligence, or computational fields with an applied focus on sport, tourism, human performance, or health, or (b) sport-, tourism-, or health-related
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Artificielle; competences en PyTorch recommandéesCandidate with a Master's degree (M2) in Applied Mathematics specializing in Statistics, Machine Learning, and Artificial Intelligence; Experience with PyTorch is
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Information Position Summary The Department of Neurosurgery is seeking a highly motivated individual with a strong background in neuroimaging analysis and artificial intelligence (AI). This position will
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growing field of artificial intelligence. Through courses and projects that focus on applied machine learning, artificial intelligence, data management, data analysis, and data visualization, students learn
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: Admission requirements: Bachelor's degree in Computer Science, Artificial Intelligence, Data Science or equivalent. The awarding of the fellowship is dependent on the applicants' enrolment in study cycle