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Field
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward
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developing new algorithmic approaches for TAPS data, interpreting the results in the context of phenotypic observations, and communicating these findings clearly to the broader team. You will prepare the
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, drawing insights and ideas for implementation. Having previous publications is a plus. Experience in designing, developing, and implementing computer vision models and algorithms. Proficiency in Python and
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in our mission to develop clinically useful algorithms, drive high-impact publications, and pave the way for personalised breast cancer treatments. Analyse data from cutting-edge technologies
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in our mission to develop clinically useful algorithms, drive high-impact publications, and pave the way for personalised breast cancer treatments. Analyse data from cutting-edge technologies
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recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms, their deficits and their rescue in genetic mouse models. This project is part of a cross-species, cross
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developed goal-sequence generalization task. The project will integrate high-density silicon probe recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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) of high-value critical assets. Through this PhD research, algorithms and tools will be further improved and developed, validated and tested. It is expected that combining the domain knowledge and the
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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