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(MOCVD). The primary aim is to develop energy-efficient 2D materials that can significantly reduce the power consumption of next-generation electronic devices, supporting the UK’s net zero goals and the
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help supervise associated PhD students. The successful candidates will join large, supportive research teams led by Profs Knight, Screen and Connelly all working collaboratively at Queen Mary. This is an
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will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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biomedical data scientist / computational biologist to join our highly collaborative team at QMUL. PhD (or close to completion) or research qualification/experience equivalent to PhD level in the relevant
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dynamics simulations to recover dynamic strain and flow fields. Candidates should hold a PhD in a relevant biology or engineering discipline and be competent with numerical simulations. We are looking for a
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. Applicants should have a PhD in Cultural Geography, Environmental Arts or a closely related field; knowledge of current climate- and ocean-related scholarship in the Blue Humanities; a track record of
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and Immigration website . Full-Time, Fixed-Term (36 months) We are looking for a highly motivated early career researcher with a PhD (or near completion) in psychology, life sciences, genetics
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-luminosity LHC. You will provide support to our PhD students and contribute to the broader activities of the group and the school. About You You will have completed or be about to complete a PhD or research
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haemostatic responses in ageing individuals. About You We seek outstanding, self-motivated, and ambitious junior researchers committed to pursuing a scientific career. Demonstrable knowledge and a PhD (or close