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at NTU are looking for a Research Fellow (RF) to carry out in research in probabilistic machine learning, causal discovery and GenAI, by exploring cutting-edge approaches such as causal representation
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engineering Computer science » Cybernetics Computer science » Informatics Engineering » Electrical engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 16 Oct
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training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning, artificial intelligence, computer vision
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intelligence and machine learning, with areas such as enzyme discovery and engineering, metabolic pathway design, genetic-code engineering, protein engineering, and the biosynthesis or biological incorporation
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Candidates should have a PhD in Electrical Engineering, or a closely related field. A strong practical embedded hardware background is essential, including experience in several of the following
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 19 hours ago
performance utilizing a variety of tools including life-cycle assessment (LCA), machine learning techniques, and/or optimization methods. This position will carry out state of the art research into the economic
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-based, and machine-learning approaches - Identifying markers of intelligent, intentional, and malicious manipulations of detection systems - Developing detection and classification methods to distinguish
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modelling of electrochemical systems, together with experience in machine learning and data-driven modelling. Research Associate: Hold a PhD in Aerospace Engineering, Chemistry, or a related discipline, or
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technologies aimed at assessing, protecting, and repairing donor livers before transplantation. This PhD project is embedded within the multidisciplinary CRISPR-CRYSTAL consortium, bringing together experts in
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application. The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology Machine Learning, AI Safety, agentic safety