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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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The project: The domain of High Performance Computing (HPC) effectively utilises massively multicore computers that facilitate the distribution of scientific workloads across thousands of compute
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learning frameworks (e.g. PyTorch, TensorFlow) and relevant libraries. Practical experience inscalable data processing, including the use of parallel computing, cloud platforms,and distributed systems
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content moderation framework for immersive 3D virtual environments, such as Roblox and Minecraft. The engineer will play a key role in building a parallelized, agent-driven exploration system and
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the delivery of a mesh generation project, funded under a recent major £7m EPSRC Programme Grant REMODEL: Advancing Parallel Mesh Generation and Geometry Representation to Enable Industrially Relevant
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. CPUs/GPUs) and their use in high-performance computing through shared or distributed parallel programming (e.g. OpenMP, MPI). Strong programming ability in C++ or a related language. Experience in
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methods will be given by the supervisory team. Work towards achieving the Objectives will run in parallel through the project, broadly along the following timeline: Year 1: literature review, desk-based
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well as community function, to be investigated in parallel. Standard geochemical analyses will be simultaneously performed to investigate interactions between the major nutrient cycles, and their impact on
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an equal-variance signal detection model to a more flexible unequal-variance model in a hierarchical Bayesian approach (Lages, 2024). Techniques used: Computational modelling, Bayesian inference, sampling
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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