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global and local settings. In parallel, the role supports international student recruitment and student body diversification by working with upstream stakeholders—such as international high schools and
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equivalent combination of education and work experience). EXPERIENCE: 2+ years of experience in GPU computing, with a focus on performance optimization and parallel programming. Proficiency in GPU programming
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and maximize model performance and generalizability. Optimize data processing and retrieval workflows to minimize latency and maximize throughput, leveraging parallel processing, caching, and other
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to operate confidently in both global and local settings. In parallel, the role supports international student recruitment and student body diversification by working with upstream stakeholders—such as
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demonstrated ability to plan and schedule laboratory workflow. Excellent interpersonal, written and verbal communication skills. Effective time management skills and the ability to work on parallel tasks
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via joint activities with EU and UK cybersecurity hubs, preparing you for careers in trusted electronics, AI security, and national critical infrastructure protection. Graduates from this programme will
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with programme ideas moving into the development stage. This work runs in parallel to the launch of a revised SSPP Strategy 2030, Shaping Global Change. SSPP is also launching a Methods Centre and a
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treatment. It is advantageous if you have previously worked with massively parallel sequencing (NGS), both in the laboratory and/or with bioinformatics, for example Single Cell RNAseq. It is also advantageous
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experimentation and thermodynamics calculations. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Develop a high
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design, pair programming, code reviews, etc. The code should take advantage of parallel processing to run efficiently. We expect that the run time will be reduced over time as (s)he improves the parallel