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Field
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psychological support to help breast cancer survivors re-establish an adaptive mind-body connection. Data collection, data management, and secure data storage for questionnaire, psychophysiology, and biomarker
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, interdisciplinary research. Our department remains at the forefront of engineering innovation, delivering sustainable solutions with global impact. As a large, multi-specialisation department, we thrive
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. The project will define new near miss and severe morbidity definitions allowing us to identify electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset
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collaborative research group of Professor André Cobb, working at the forefront of foldamer research and cutting-edge synthetic methodologies (for information about the group, please visit http
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knowledge and tools for non-equilibrium flows for hypersonic vehicles. The research will provide unique and high-quality experimental data for expanding high temperature flows. Alongside this, the proposal
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
investigate the large area production of graphene, BN, MoS2 and other layered materials, optimize their transfer process in view of their application in energy, electronics and photonics. This will include
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and promote open science and use transparent reporting and data handling practices according to the highest standards. Being responsible for the day-to-day administrative duties and the recruitment
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a project aimed at developing more exoelectrogenic cyanobacterial strains. The project involves the creation of large mutant libraries of cyanobacteria and automation of screening for electroactivity
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kidney cancer research. This is an exciting opportunity to contribute to a large-scale, collaborative project investigating the genomic evolution of kidney cancer, using a uniquely rich cohort of patient
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electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset for the first time. This will allow us to work out the best vital-sign-based early warning score