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Field
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of peptide design and chemistry, computational methods (machine learning, deep learning, genetic algorithms), microbiology, synthetic biology, and related areas essential to developing novel
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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in programming (e.g., Python), data analysis, and machine learning, and a curiosity about applying computational methods to diverse domains such as biology, psychology, and medicine. Candidates
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We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning
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at the intersection of sensor data collection, machine learning, and real-time decision-making. Specifically, the candidate will contribute to projects focused on developing advanced machine learning models to quantify
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The University of Alabama, Department of Electrical and Computer Engineering | United States | about 2 months ago
. Nathan Jeong shjeong@eng.ua.eduAdvanced Signal Processing and Machine Learning Algorithms for Autonomous Vehicles, Prof. Shunqiao Sun ssun21@eng.ua.eduTransportation Electrification and Power Distribution
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integrated with the NiMARE (NMA) software project. To be considered you will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain
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to support a diverse and inclusive university in which to work, study, teach, research and serve. No person shall be denied employment on the basis of any legally protected status or subjected to prohibited
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will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain imaging data and possess sufficient specialist knowledge in brain
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candidate will play a key role in designing and implementing innovative solutions at the intersection of sensor data collection, machine learning, and real-time decision-making. Specifically, the candidate