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achieved by combining state-of-the-art algorithms from multiple domains such as evolutionary algorithms, reinforcement learning, and control theory. The main responsibility of the successful applicant will
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to understand cancer outcomes, the planned work will address the need to evaluate data from multiple patient groups that are under-represented in clinical trials, including those from Black, Asian and Minority
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sequencing methods, ELISA. Being highly motivated, strong collaborative spirit, with excellent communication skills. Having demonstrated organisational skills, initiative and ability to work independently
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own academic research and administrative activities. This involves small scale project management, to co-ordinate multiple aspects of work to meet deadlines. The post will be based in the Department
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, metabolomics). Significant practical laboratory experience [e.g. nucleic acid extraction techniques (both manual and automated), developing real-time PCR assays and gene sequencing methods, ELISA. Being highly
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, an understanding of evolution of foundation models, and a good grounding in multimodal learning, including fusion and alignment. How to Apply Please submit an application via the Queen Mary Portal and upload a copy
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drug and disease research in multiple projects in the group. The candidate is expected to lead a drug development project and support other group projects. This will include lab experiments, analysing
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complex research projects involving multiple interdependent components. Experience in programming (python) and applying AI-assisted technologies to streamline research and analysis workflows is highly
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interdisciplinary research including experimental field trials, social research, and ecological monitoring across multiple sites. The post-holder will lead the project’s ecological research components and contribute
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fundamental research Alignment with our core values What we offer The MQO group is young but yet very ambitious research team exploring quantum phenomena in large scale and complex systems, from