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of teaching quality. We strive in publishing in top-tier conferences and journals. Some of the areas you will work on are: Designing and developing novel algorithms for detecting and defending against
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-throughput multi-omics data (16S rRNA, metagenomics, or metatranscriptomics) in environmental or biological systems. Computational Modelling: Proven experience in computational modelling, algorithm development
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will support their operation and management alongside the project leadership team. The project will build on work being undertaken in the regional STEP-UP (https://step-up.ac.uk ) project funded under
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components, including model runtimes, memory managers, schedulers, accelerator kernels, isolation mechanisms, and distributed communication, which significantly increases their trusted computing base and
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inversion algorithm and micromagnetic CRM database to interacting particle assemblages, and contribute to a user-friendly, open-access ChemPI web app. In the final phase you will apply ChemPI, with Oxford
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develop novel algorithms and policies for high-DoF hands and validate them on real hardware. In doing so, you will collaborate with a team of expert researchers in robotics, computer vision and machine
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Systems via Proof Certificates, and focus on the design, development, and application of Safe RL algorithms as well as their verification via Proof Certificates, including monitoring and shielding of cyber
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attribution studies, including analyses during heatwaves. The role involves using and developing methods such as case-crossover designs, distributed lag non-linear models, Bayesian hierarchical models
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as close as possible to data sources and end users for a distributed, adaptive, sovereign, robust and energy-efficient paradigm of AI deployment. Imperial College is consistently in the top 10 world
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of cardiovascular health. Further information on the research themes: https://www.imperial.ac.uk/bhf-research-excellence/ . Recruitment is open to expertise in all relevant areas including discovery science and