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, distributed control, formation control, perception, and decision-making in complex environments. Design and implement data-driven approaches, including machine learning, reinforcement learning, surrogate models
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/Resume. Required Education and Experience PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field. Preferred Qualifications Strong publication record in top-tier AI
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collection, data organization, and project execution to publication. Other Duties Other duties as assigned. Additional Information Machines or equipment used in the performance of essential duties Computer
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Abilities: Ability to effectively use a computer and applicable software (Microsoft Office, GraphPad, Zoom, etc.) Ability to multi-task and work cooperatively with others Animal handling (adult horses and
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students. Designing novel experiments and concept in several basic, translational, and clinical projects in metabolic diseases and pregnancy disorders Good computer literacy including databases, standard
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, integrates, and evaluates innovative solutions in autonomous systems, including artificial intelligence (AI), machine learning, robotics, control systems, sensing technologies, and related disciplines
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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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for high-dimensional dependent data, and data sketching approaches for massive data. Opportunities to Contribute: Develop statistical/machine learning methodology for multi-modal imaging data integration
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through which immune-brain interactions contribute to physiological and behavioral outcomes. Current research interests include understanding how traumatic stress influence's immune function and
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with stakeholders. QUALIFICATIONS Doctoral degree in Computer Science, Electrical/Computer Engineering, or a closely related field. Foundation in network security for 5G/6G and O-RAN, including TLS 1.2