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information from ‘deep tissue phenotyping’ datasets. The successful applicant will have significant experience working with machine learning algorithms. They will have strong Python programming skills and
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the swabbing procedure. Your key role within the team will be to develop a robotic swabbing system, conduct user studies for efficacy evaluation, and develop automatic swabbing control algorithms. You will have
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team. You will lead in the design and implementation of statistical and computational algorithms of different datasets, and implement novel algorithms within the framework of existing code, providing
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development of algorithms using modern machine learning libraries (mainly pytorch) and over the course of the project duration, the developed algorithms is expected to reach a medium to high TRL. The applicant
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algorithms. These algorithms act as perfect digital lenses, with no image degradation from aberrations, and provide a fantastically detailed, information-rich view of any sample being imaged. Applications
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thesis shall highlight the proposed risk embedding technique into MASs path planning algorithms, enabling them to realise guaranteed, conservative, yet risk-feasible trajectories for efficient state-space
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, and maintaining software systems to support these research projects. This includes building data pipelines, developing algorithms, and ensuring that data is stored efficiently and is accessible to all
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to make one appointment in the area of applied neuromorphic algorithm design. You will join the International Centre for Neuromorphic Systems - and be part of the wider pan-university community
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maintenance, production efficiency, and quality control. While the benefits of ML are significant, its adoption also introduces risks such as data privacy concerns, algorithmic bias, model transparency issues
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foundation models, multi-modal learning algorithms, generative models, and large language models [1], have made seen remarkable advancements in the field of healthcare. It can lead to more accurate diagnosis