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future autonomous instrument control and self-directed experimentation will be developed, recognizing the challenge presented by the integration of multiple complex systems. Coding and user interface
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both functional and technical domains. Collaborates with business process owners to translate business needs into robust system solutions and effective process enhancements. Designs, develops, and tests
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the modelling, simulation and analysis of the large, complex and dynamic systems (e.g. cyber and physical systems). The PhD student will join the Sheffield Control and Power Systems (CAPS) Laboratory (https
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Autonomous Scalable Knowledge Extraction and Decision Making for Complex Systems and Dynamic Environments School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof
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date (mobility rules of the Marie Skłodowska-Curie program) Masters degree in electrical/electronic engineering, computer engineering, computer science, physics, or related fields Coursework in
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systems. The role designs and delivers impactful training that improves efficiency, manages risk and supports compliance, working closely with process owners and change teams to embed best practice across
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(FSS) Centre of Excellence (CoE), by: Managing complex, cross-functional projects with strong governance and execution discipline Optimizing systems and processes to enhance efficiency, scalability, and
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a rich experimental environment that encompasses both basic and translational research For an overview of our recent publications, please visit: https://med.virginia.edu/le-lab/publications
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concern. According to the World Health Organization (https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance), bacterial AMR alone was directly responsible for 1.27 million global deaths
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healthier for everyone in our community! Clinic Background This position is based in a hospital‑based outpatient neurologic rehabilitation clinic with a strong focus on complex, specialty care. The clinic