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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse
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Qualifications: Completed doctoral studies – PhD in bio-resource technology, practical implementation of Machine Learning, or a related field. Strong knowledge of Food security theory. Understanding of principles
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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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Adaptive Learning in Brain-Robot Interactions School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year
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practical tools deployable in real-world clinical settings. This work is central to a multidisciplinary collaboration bringing together experts in neuroscience, machine learning, and clinical informatics
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. Research Associate in Bioinformatics and Machine Learning Applications to Stem Cell Bioengineering The School of Biomedical Engineering at the University of British Columbia, Vancouver campus is seeking a
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of Adjunct instructor to teach in the PhD program in the 2026/2027 academic year. This position, in conjunction with three other faculty, will teach a portion of the PhD course "Emerging Topics in Operations
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machine learning, distributed systems, programmable hardware, statistics, and applied mathematics. Our culture is steeped in the idea that we will never stop solving; we’re looking forward to supporting
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 9 days ago
will focus on the following main tasks: 1) Machine-learn optimal reaction coordinates for the barnase-barstar complex, starting from ~0.1 millisecond high-dimensional MD (generated by a previous PhD
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line