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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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stress resilience. Applicants must be highly motivated, with a PhD in plant biology or a related area. PhD students about to submit their thesis in a relevant area will be considered. The successful
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You To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in a relevant subject (molecular microbiology, cell biology
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that the microbiome may play in providing stress resilience. Applicants must be highly motivated, with a PhD in plant biology or a related area. PhD students about to submit their thesis in a relevant area will be
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-century material from mostly unpublished sources in UK archives; contribute to physical and digital exhibition curation; produce high-quality academic publications; contribute to academic symposia; and
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for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets
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computational biology and mathematical spatial analysis via independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics, computational biology, data
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will also develop skills in mathematical modelling and spatial analysis via independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics
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candidate will hold a PhD in physics, biophysics, physical chemistry, engineering, or a related area, or have submitted a PhD thesis prior to taking up the appointment. The research requires strong interest