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Field
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algorithms and parallel/distributed variational algorithms in AI/ML for application workflows and large-scale HPC and QC systems Develop quantum machine learning (QML) algorithms for optimization of multi
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with compiler level languages, accelerated computing (preferably with OpenMP or OpenACC) and distributed computing (MPI). A thorough understanding of the particle-in-cell algorithm, its inherent
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processing algorithms from concept to implementation. Eligibility to obtain a United States SECRET clearance (or higher) is required for ongoing employment in this position Minimum Qualifications: 1
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the power of cutting-edge digital technologies to implement and manage FAIR (Findability, Accessibility, Interoperability and Reusability) environments for data management and algorithm preservation and
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proficiency in information technology, with particular emphasis on the design of information systems, distributed and mobile systems, cloud solutions, virtualization, containerization, operating systems
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), Dedicated HPC solvers (domain decomposition, parallel/distributed computing), Formulation and solution of optimisation problems (automation, optimal structural design). The developments will follow open
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for complex scientific problems Designing algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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trustworthy medical AI? Deep models already outperform humans on many benchmarks, yet in the clinic they remain black boxes: radiologists cannot see why an algorithm flags a lesion, and AI engineers cannot tell
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as