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Posting Close Date Qualifications Minimum Education and Experience ● PhD in Computer Science or related discipline. ● Has a proven track record of excellence in artificial intelligence/machine learning and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
of proficiency in either R or Python in the areas of machine learning, deep learning, statistical analysis, computer vision, and/or graph analysis Experience with data engineering to create data
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management, analytics, machine learning, and artificial intelligence. Its objective is to contribute to the advancement of scientific knowledge in the field of data-centric systems by addressing the challenges
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initiation latency, movement speed, gait characteristics, postural control, motor variability, and other behavioural descriptors. ESSENTIAL REQUIREMENT PhD in machine learning, artificial intelligence
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-augmented generation (RAG) approaches Systems and mathematical modeling of biological or complex systems Natural language processing and machine learning Data harmonization and integration Record of research
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of Nursing: teach, participate in service-related activities that support the school, and engage in clinical scholarship. In addition, as an advanced practice nurse educator, the faculty member is encouraged
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paradigms. We are also leveraging several analytical tools such as computational modelling and machine learning. As a Research Assistant, you will help collect, analyse and interpret EEG data collected in
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24 Aug 2026 Job Information Organisation/Company Johannes Kepler University Department Institute for Machine Learning Research Field Computer science Researcher Profile Recognised Researcher (R2
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CRC2 & Mitchell Funded Tenure-Track Faculty Positions in Supercomtuping and High-Performance Computi
Queen's University - Electrical and Computer Engineering, Smith Engineering | Kingston Downtown, Ontario | Canada | about 9 hours agoprovided by the Engineering Teaching and Learning Team, the Queen’s Centre for Teaching and Learning, the Department, and Smith Engineering. The Department of Electrical and Computer Engineering has 36 full
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, including gas turbines and combustion engines. We combine advanced computational fluid dynamics, theory, machine learning, high-performance computing, and experimental methods to investigate and model complex