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Design of a Fault Detection System for AI-Assisted Adversarial Attacks on Industrial Control Systems
Design of a Fault Detection System for AI-Assisted Adversarial Attacks on Industrial Control Systems School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Aryan
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 1 day ago
earned a PhD in Religious Studies or a cognate discipline, with a clearly demonstrated record of excellence in research and teaching. The successful candidate will have an established international
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scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments. About the role We
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or neuroscience and extensive experience in quantitative methods will also be considered. The candidate should have good knowledge of one programming language used for computational modeling
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. • Coordinate PhD student annual academic reviews, including creating timelines, template language, and documentation in conjunction with the PhD Program Committee and PhD Program Director. • Track
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an asset. Applicants must hold a PhD or equivalent, preferably in International Relations or Political Science. They must have experience with research, teaching and service commensurate with a tenured
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(including PhD students and research staff) to conduct research work on AI-assisted design; Support the validation of large language models for generative metamaterial design; Assist in building and testing AI
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to some teaching to the CDH MPhil programme and may also engage with some doctoral training. They should expect to become an engaged member of the CDH research community. Applicants may have a doctoral
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focused on primary human samples derived from blood or tissues in individuals with characterized infection or tumor histories. Using a combination of bioinformatic and computational approaches, we will
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The post of Research Associate in Large Language Models for Process Automation will contribute to the development of an AI-powered framework for risk assessment and safety in continuous chemical