42 phd-position-wireless-sensor-networks Postdoctoral positions at Oak Ridge National Laboratory
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at the intersection of quantum information science and fundamental materials physics. The research program focuses on understanding the fundamental limits of spin-based quantum sensors as probes of magnetic and
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automation, machine learning, mobile robotics, process control, sensor processing, machine vision, and/or human machine interaction. This position will require working with external partners, corporations, and
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computations, sparse tensor problems, and sparse network problems, as well as their interconnections. This position offers a unique opportunity to make significant theoretical and applied contributions
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this role, you will study buried interfaces in monolithic 3D heterogeneous integration (M3D HI) systems, with a particular emphasis on vertically stacked 2D/3D semiconductor heterostructures. This position
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visual representation and analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division
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of researchers, technical professionals, and software developers focused on conducting research in world-class facilities and deploying science-based knowledge in real-world applications. The position supports
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. This project uses crystal growth and physical property measurements to develop, understand, and control new and emerging materials. This position resides in the Correlated Electron Materials Group in
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. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, industrial engineering
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development. Basic Qualifications: A PhD in computer science/engineering, electrical engineering, data science or a related field completed within the last five years. Experience of AI and efficient computing
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integration and utilization. Group initiatives encompass innovative sensor technologies, advanced modeling techniques, and precise control mechanisms specifically designed for the grid edge. Research promotes