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Field
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We seek to recruit a Research Associate/Fellow to join our team developing a groundbreaking technique based on autofluorescence (AF) imaging and Raman spectroscopy for detection of positive lymph
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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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) 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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, 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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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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imaging data, and the development of Large Language Models of biological sequences and their interactions. A position is available within the group to further advance these models and use them to extract
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enable the development and operation of new algorithms and software to solve leading-edge research problems. You will find this work exciting if you: Want to help build and maintain some of the largest
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multidisciplinary R&D team and leading scientists from Oxford and Stanford, contributing to the development of scientific research, you will play a pivotal role in shaping the future of fatigue detection and
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consists of three major parts: sensor printing, circuit design and integration and developing of an AI algorithm and using it to teach the sensor to selectively measure desired gases . In this role, you will