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researchers Grant writing experience Experience with high performance computing (HPC) and deep learning frameworks like PyTorch Experience developing parallel algorithms and scalable workflows for HPC resources
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workloads. Conduct research on language front‑end abstractions, mixed‑precision modeling, heterogeneous parallelism, and MLIR-level transformations. HPC System Co‑Design: Work with domain scientists and
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following treatment. NEWDAY-ABC is a hybrid intervention-implementation trial that will be carried out at four sites across Yorkshire and Greater Manchester. The parallel process evaluation will assess
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information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care
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using quantum information principles, investigate fundamental quantum physics using the neutron interferometry facility at the NIST Center for Neutron Research, explore parallels between atom and neutron
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programming language to solve computational problems Awareness of computational infrastructure and its upkeep Ability to work on multiple projects in parallel and set priorities Willingness to provide training
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Software Engineering. The department will accept all qualified candidates but is particularly interested in applicants with experience in quantum computing, parallel computing, databases, or web development
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. Qualifications: Familiarity with machine learning interatomic potentials, CPU and GPU parallelization, knowledge of LAMMPS and molecular dynamics, experience with first principles calculations of dielectric and
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massively parallel FFT-based simulation platform for polycrystalline plasticity, enabling efficient simulation of the mechanical response of realistic 3D microstructures. These simulations will be used
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less). To address this technological bottleneck, we are developing a new technology platform--next gen protein sequencing--based on large-scale, massively parallel, single-molecule peptide sequencing