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We are seeking a motivated and Talented experimentalist for a full-time Postdoctoral Research Assistant in Modelling of Quantum Computing Control Systems within Professor Ares’ and Professor
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challenge, making energy-efficient computing a critical research priority. This project addresses this challenge through a novel co-design approach that simultaneously optimizes both hardware and software
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computational methods to optimize wind farm performance, which in turn generates clean energy that can power future HPC systems. What you would be doing: You will design, implement and test energy-efficient
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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applicants for a 6-month paternity leave replacement who have a strong interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental
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for their expression in plant colonizing bacteria and integrating them into the chromosomes of appropriate chassis. Control systems will be designed to restrict expression to target plants and ensure optimal expression
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inland, short-sea, and high-seas shipping routes. The project seeks to deliver industry-relevant tools that enable optimal design and operation of greener vessels, backed by real-world demonstrations
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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emphasis on research infrastructure and technology rather than preparation for an academic career path. You will be involved in research, but more focused on learning and improving how computing, workflows
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solutions ; High -performance computing systems to support specialized AI and LLM, and to empower the development and refinement of advanced algorithms for 6G communications, optimal grid management