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member to begin Fall 2026. We seek candidates with a PhD in Computer Engineering, Electrical Engineering, Computer Science, Information Technology or related fields whose research aligns with strategic
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Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through
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North Carolina Agricultural and Technical State University | Greensboro, North Carolina | United States | about 5 hours ago
education, research, discovery, and innovation. The College houses the departments of Applied Engineering Technology, Biology, Built Environment, Chemistry, Computer Systems Technology, Mathematics
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University, Tyndall National Institute, and Seagate Technology, one of the global leaders in data storage and photonics innovation. Four PhD students will be based at ATU Donegal and will join the
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Engineering and Mechatronics. The Proposed PhD thesis topic: “Intelligent Diagnostics of Electrical Machines through AI-Enabled IoT Systems: Design of Custom Embedded Hardware and Protocol-Aware Architectures
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills as well as the absolute
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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requirements: Master’s degree or equivalent preferably in machine learning or equivalent fields. A Master’s degree in computer science/statistics/applied mathematics/electrical engineering can also be considered
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skills and experience: Essential criteria PhD or equivalent (or thesis submitted*) in at least one of the following subjects: Computer Science, Machine Learning, Biomedical Engineering, Medical Imaging