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for secure and resilient systems; privacy; secure sensing and control in critical infrastructures) Candidates with a PhD in Electrical Engineering, Computer Engineering, Computer Science, or other closely
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computing, and to pursue new strategic research initiatives under the Department/Faculty/University. Requirements: Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 5 days ago
– Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics
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for farm-farm interaction Development of coupled LES and aero-elastic models using the actuator line method Analysis and design of wind farm control through LES and machine learning Scientific publication
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knowledge of power system security and machine learning being crucial. The Associate will primarily work alongside National Grid engineers to integrate the machine learning backend of the intrusion detection
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Technology (IST) has 44 full-time faculty members with research foci in cybersecurity, data mining and machine learning, natural language processing, human-centered computing, and computing and engineering
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, technical depth, and a strong track record of applied research in Computational Biology, Structural Biology, Protein Engineering, Machine Learning, or a closely related field. Strong understanding and
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 3 hours ago
PhD or advanced Master’s program in economics, finance, business analytics or related fields. The chosen candidates will also gain valuable experience analyzing large data sets and learning skills in
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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
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the leadership of Principal Investigator Dr Andrew Siemion. Listen's interdisciplinary research has synergies with many of the department's research priorities, including exoplanet studies, machine learning