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Position Control Number 6155 Suffix 00 Contingency Code Not Applicable FTE 1.0 Contract Basis Fiscal Year Anticipated Contract Start Date 06/29/2026 FLSA Status Exempt Tenure Tracking Non-Tenure Track Rank
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control theory Help mentor graduate and undergraduate students Participate in other ongoing research activities within the areas of connected and automated vehicles and intelligent transportation systems
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level consistent with the program's curricular offerings. Courses may include Legal Studies 10- Introduction to the Legal Process, theory themed courses, public law and institutions themed courses, law
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) a European master's degree in Computer Science or Electronics Engineering, with excellent ('honors'-level or above) grades. You have a strong foundation in control theory, deep learning or computer
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that this PHD research will explore with regard to healthcare productivity: the importance of operational variables, the impact of volume, routing patients through healthcare systems, quality control, and
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, Professional Practice, Building Construction, Sustainability, Research Methods, Theory, Environmental Control Systems. Faculty Tenure Track No Faculty Rank Non-Tenure Track Position Number 4A6161 Department
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oral and written communication skills in English. Candidates without a master’s degree have until June 30, 2026 to complete the final exam. Desired qualifications: Background in probability theory and
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Control Number 0364 Suffix 00 Contingency Code Not Applicable FTE 1 Contract Basis Academic Year Anticipated Contract Start Date 08/17/2026 FLSA Status Exempt Tenure Tracking Non-Tenure Track Rank Assistant
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George Washington University | Washington, District of Columbia | United States | about 19 hours ago
programs, including a PhD in Global Health Sciences, and Masters in Public Health (MPH) in: Global Health Epidemiology and Disease Control; Global Health Program Design, Monitoring & Evaluation; Global
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on the intersection of robotics and control theory. Project description: This PhD project aims to develop learning‑based methods that combine expert demonstrations with experiential reinforcement learning to enable