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movement; (iii) generate benefits for both society and the environment by guiding possible mitigation strategies; and (iv) drive technological progress through the development of novel algorithms
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and distributed memory programming tools (e.g. OpenMP, MPI) Accelerator programming (e.g. CUDA, OpenCL, SYCL) Serial and parallel debugging and profiling Parallel numerical algorithms and libraries
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programming and evolutionary algorithms for scheduling. A high level of motivation and commitment to successfully completing your doctoral studies within the planned timeframe. Cooperative, team-oriented, and
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prediction tasks. Knowledge of a wide range of statistical tools and clustering / prediction algorithms is required. Experience of using foundation models and generative AI would be an advantage. Specific
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discovery, and deep-learning algorithms • Neutron scattering and advanced characterisation techniques The successful candidate will work closely with other PhDs and postdocs involved in similar investigations
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to clients, and carers’ scheduling to allocate the time for clients’ visits. Various objectives and requirements of the variety of home-based services have to be taken into account considering carers’ and