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requirement Work plan: The candidate will carry out R&D activities within the scope of the 2022.06672.PTDC project, namely: 1) Review of the literature on adaptive mesh generation algorithms for singular
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domains. The successful candidate will: Develop algorithms to model team performance based on interpersonal (e.g., monitoring, communication) and cognitive (e.g., shared mental models) processes. Design an
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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genetics and genomics, with expanded interests in computational biology, functional genomics, and neuroscience. Example projects within the university and with external partners: • Noncoding Variation in
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, Experimental Research, Game Theory, and Artificial Intelligence. Some of the research topics that excite us as a group include: (i) Ethics of AI and Automation; (ii) Social Media Analysis (iii) Algorithmic
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magnetometry measurement and analysis of the Nab spectrometer magnetic fields, help develop the BL3 DAQ and algorithms, carry out Monte Carlo simulations for Nab and BL3, and help undergraduates at EKU finish
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or accelerated acquisition and reconstruction algorithms will be highly valued. Instructions Interested candidates should apply via Interfolio link with their CV (including a full list of publications), a
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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data management sufficient to create, transform and integrate data in a variety of resolutions and formats. Analysis will include running machine learning algorithms (e.g., Random Forest, CART) and