36 parallel-and-distributed-computing-"LIST" positions at The University of Manchester in United Kingdom
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Department: Electrical and Electronic Engineering Title: Intelligent Distribution System Operation for Low-Carbon Power Systems Application deadline: All year round Research theme: Power and Energy
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, nonlinear dynamical systems, robotics, and formal methods to develop principled models and algorithms for distributed decision-making in complex and uncertain environments. Your research The candidate will
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on precisely defined chemistry, underpinned by measurement of atomic and isotopic composition/distribution with extreme precision e.g. isotopic implants in Quantum Technologies. Investigation of failure
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distributions and ensure fuel operates within design limits. The aim of this project is to establish a robust, validated framework for neutronics and thermal analysis of prismatic HTGR cores, integrating Monte
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PhD Studentship available on the RAINZ CDT programme at The University of Manchester. Project Overview Abstract: Offshore wind and marine energy assets operate in harsh, inaccessible environments
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PhD Studentship available on the RAINZ CDT programme at The University of Manchester. Project Overview Abstract: Complex software-driven systems, including autonomous robotics, are typically
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in porous geological formations. The successful candidate will develop and implement computational models, validate them against experimental or field data where available, and contribute to the design
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Engineering, Computer Science, Physics, Mathematics, or a related discipline. Applicants should also demonstrate evidence of programming experience. Experience and background in the area of Robotics or Cyber
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Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline. Applicants should also demonstrate
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in the groups of Dr Florence Hardy and Prof Anthony Green, University of Manchester, as part of the cross-institutional BioAID Doctoral Training Programme, including world-leading experts from Queen's