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Are you passionate about developing numerical algorithms or high-performance software for scientific computing? Do you have expertise in numerical linear algebra or experience with large-scale
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of algorithms for natural language understanding, structured command generation, and domain-specific model adaptation or fine-tuning. Integrate NLP and speech technologies (ASR/TTS) into a unified tactical signal
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numerical algorithms or high-performance software for scientific computing? Do you have expertise in numerical linear algebra or experience with large-scale computing and want to broaden your skills? Would
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strengths in global health research, bringing cohesion to the distributed community of Oxford scholars working in this area, transforming the visibility of Oxford Global Health externally, and championing key
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research, bringing cohesion to the distributed community of Oxford scholars working in this area, transforming the visibility of Oxford Global Health externally, and championing key challenge areas
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resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge on control is highly preferred. Have experience and commitment to supervising student
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industrialise algorithms designed to simulate and optimise the operation and design of aircraft systems, subject to complex, real-world constraints. You will join a growing team of engineers working on a range of
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Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm
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benefit society by advancing technologies that will underpin the design of the next generation of transport aircraft. Specifically, you will develop, test, and industrialise algorithms designed to simulate
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Wearables & Healthcare Systems Theme 3 Algorithms for Privacy, Security and Provenance Theme 4 Clinical Innovation & Translation Connected medical devices are increasingly employed in the drive towards