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including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
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engineering. We aim to unravel the logic of genome organisation and metabolic control—with the bold vision of building synthetic life. In this role, you will develop and apply computational methods to analyse
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writing skills Evidence of publication track record Extensive experience and expertise in version control (e.g., Git) and reproducible research practices * Please note that this is a PhD level role but
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for Translational Bioinformatics is a team of computational biologists, software engineers and data scientists located within the Digital Environment Research Institute (https://www.qmul.ac.uk/deri/) at Queen Mary
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to the clinic The post holder will be based in the Department of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers
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to the clinic The post holder will be based in the Department of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers
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workflows and validate the established systems in tandem with clinical partners. About You You will possess a PhD (or be nearing completion) in mechanical, electrical, or biomedical engineering, or a related
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health-related claims. This 6-year Discovery Award will critically explore how contemporary seek to control and regulate unproven, disproven, or misleading health-related claims. Bringing together
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this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in Physics, Optical engineering, or a closely related field (award received or thesis submitted and
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to answer pressing biological questions across development, cancer and immunology. We work shoulder-to-shoulder with biologists, clinicians, engineers and data scientists, providing an exceptionally