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: Design and optimization of graphene edge to edge tunning device structures, and electronic signal detection. Design and test of microfluidic structures in combination with the tunneling device. Taking
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systems, optimal control and mathemathical statistics is strongly desired You have documented potential in research and education, shown through publications, projects, or teaching activities You are
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
underlying cancer disparities and drivers. Opportunities available to T32 Postdoctoral Fellows - Mentoring by faculty with extramurally funded cancer control research programs - Networking with other post
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 20 days ago
underlying cancer disparities and drivers. Opportunities available to T32 Postdoctoral Fellows - Mentoring by faculty with extramurally funded cancer control research programs - Networking with other post
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conferences. Level of Decision Making: The postdoc will design and optimize experiments, particularly for Next Generation Sequencing workflows, including library preparation and data analysis. They will
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. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement learning, and Data-driven modeling and control. The Post-Doctoral associates will be based at NYU Abu Dhabi and
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information about our research group can be found at: https://autonomousrobots.nl/ Job requirements We are looking for a candidate with: A PhD degree in Robotics, Control, Aerospace Engineering, Mechanical
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control, and data science, at the Department of Mathematical Sciences. About us The Department of Mathematical Science provides a creative, dynamic and innovative environment where research, education, and
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, laboratory testing, greenhouse experiments, and agronomic validation. Key Responsibilities Develop and formulate new simple and complex fertilizer products Contribute to the optimization of fertilizer
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motivation to enhance our multidisciplinary research at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control