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research and publications in one or more of the following areas: Item response modelling Modelling of process data (e.g., response times) for competence tests Application of machine learning methods in
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 hours ago
emerging technology and computer applications (Word, PowerPoint, Excel, Canva), Adobe Creative Suite (InDesign, Illustrator, Photoshop, Premiere), and social media platforms and management programs (Buffer
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of Construction Management or Computer Aided Design. 3. Actively engage students in critical thinking, meta-cognitive processes, and interpersonal workplace skills. 4. Model and cultivate open minded inquiry
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Mixed Reality. This research combines physiological time series analysis (such as or similar to EEG, EMG, EOG), machine learning, and real-time system design for intelligent interaction systems
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performance analysis, graph-driven deep neural networks, data-efficient machine learning, self-supervised learning, reinforcement learning, online learning, and meta-learning with applications
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on machine learning, and developing and applying simulation methods and models for equilibrium and nonequilibrium molecular dynamics simulations. You will model meta-lactamases enzymes involved in resistance
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for scalable deployment. Familiarity with machine learning techniques. Familiarity with Ecological Meta-Language (EML). Experience with R Shiny, Python or others. Knowledge of web content management systems
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multiple Asian cohorts. The position focuses on data harmonisation, statistical genetics, and developing and validating machine learning cancer risk models. Key Responsibilities: Data harmonization
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methods based on machine learning, and developing and applying simulation methods and models for equilibrium and nonequilibrium molecular dynamics simulations. You will model meta-lactamases enzymes
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental