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years and in the relevant areas of Machine Learning / Artificial Intelligence, Credit Risk Modeling and Operations Optimization Modeling; The candidate must have strong programming skills in Python, and
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including: Multi-scale Modeling / Computational Biologist / Bioinformatician – Research Scientist Artificial Intelligence (AI) / Machine Learning (ML) – Research Scientist Experimental Immunologist – Research
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at the interface of biological physics, agent-based simulations and machine learning to turn quantitative imaging data into a mechanistic, testable model of spindle positioning. In particular, we expect
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for collaboration. You will also have the opportunity to develop your own research project aligned to the interests of the MND group. This could include new machine learning models or exploring a particular aspect of
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular
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/ThreeBodyTB.jl), cluster expansion, classical potential development, and machine learning. In addition to work on specific problems, I work on developing new first principles-based modeling approaches, including
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. Into the second year, the project moves toward methodology refinement and Machine Learning integration. The student will execute a more ambitious cycle with a complex alloy system and integrate machine learning
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, aiming to enable faster, cheaper, and more robust production through machine learning, multi-scale modelling, and advanced process simulation. The successful candidate will be based at the Bristol
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Institute on advanced machine learning projects that use historical behavioral data to predict outcomes and inform strategies to improve engagement and solicitation effectiveness. Additionally, the Lead Data