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Contract: Full Time/Fixed Term for three (3) years.Supervisor:Dr Mohamed Lamine Faycal BELLAREDJ, Assistant ProfessorDepartment of electrical engineering, Universite de Moncton (Moncton campus)Email
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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, biologists, and engineers. You will also have the opportunity to present your research at international conferences, expanding your network and gaining valuable experience in scientific communication
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, such as engineering, physics, statistics, or mathematics (minimum requirement is a four-year Bachelor’s degree with honours) The research area The AITHYRA-CeMM PhD Program will focus on the thematic areas
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State University of New York University at Albany | Albany, New York | United States | about 10 hours ago
, New York State's capital, the University is convenient to Boston, New York City, and the Adirondacks. Job Description: The Center for Technology in Government (CTG UAlbany) at the University at Albany
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your professional network. You will also have opportunities to present your work at leading conferences, engage in international collaborations, and develop a strong professional profile in computational
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for distribution electric propulsion. Who we are looking for We are looking for enthusiastic, self-motivated applicants with first-class degree in Electrical Engineering, Aerospace Engineering or Computer
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welcomes applications from individuals with a master’s degree in the following fields: Computer Science Mathematics Natural or engineering sciences or an equivalent degree, interested in High-Performance
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with your CAPeX colleagues, you will develop, engineer, and test new experimental approaches which push the state-of-the-art fast and sensitive product detection in electrochemical and electrocatalytic
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directions will be pursued to enhance column generation using machine learning. The first line of research focuses on improving scalability by using Graph Neural Networks to identify and eliminate non