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increasingly complex compute- and data-intensive problems in science and engineering on high-end parallel and distributed computing platforms. The selected candidate will play an integral part in the group's
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notes, and produce well-researched notes. Strong organisational and time management abilities; ability to self-motivate; manage a range of tasks in parallel; and reprioritise effectively in response
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applications. The research will examine how key parameters—such as printing speed, toolpath strategy, material rheology, and geometric complexity—influence interlayer adhesion. In parallel, the project will
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algorithms * Parallel algorithms and distributed computing * Parameterized complexity and structural graph theory * Random structures and randomized algorithms * Sublinear and streaming algorithms
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device efficiency. There will be an opportunity to learn the tools required for parallel computing using graphical processing units. This will be used to maximise the computational throughput to enable
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: Nonlinear dynamical systems modelling Large-scale simulations and high-performance computing Parallel programming and optimisation techniques These are high-value skills with applications across academia
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stomata (2). In parallel, you will measure gas exchange in these plants, allowing you to explore how guard cell shape influences stomatal performance, both at the level of individual stomata and the whole
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cells, most notably immune cells. This project will investigate how cells coordinate these parallel nutrient scavenging approaches. The aim is to uncover the molecular mechanisms by which they talk
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provide powerful tools to improve the quality and efficiency of data-driven models. In parallel to the development of data-driven models for dynamical systems with geometric structures such as Hamiltonian
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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