21 structures-"https:" "https:" "https:" "https:" "https:" "https:" "The University of Manchester" positions at University of Manchester
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commitment to continuous professional development. Our Commitment to Inclusion The University of Manchester is committed to equality, diversity and inclusion and welcomes applications from all backgrounds. We
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of Manchester, and is funded by the University of Manchester and the UK Engineering and Physical Sciences Research Council (EPSRC). The role of the post-doctoral research associate is to engage in developing new
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the structure and function of the blood-brain barrier in vitro. During this position, the post-holder will undertake a range of activities including establishing in vitro models of the blood-brain barrier using
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The University of Manchester (www.manchester.ac.uk) is one of the largest single-site universities in the UK, with one of the biggest student communities. In total, 25 Nobel Prize winners have
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practice. The post-holder will be based at The University of Manchester in the Politics Department. This is an excellent opportunity for a specialist in human trafficking and forced labour studies. We
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for this post. The appointment will always be made on merit. For further information, please visit https://www.ce.manchester.ac.uk/ The University of Manchester values a diverse workforce and welcomes
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-focused PDRA position, will be based at the University of Manchester, but co-supervised by lead researchers at both the University of Manchester (Professor Catherine Powell) and the University Edinburgh (Dr
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Applications are invited for an enthusiastic and proactive Research Technician to join the Bertuzzi’s group at the Manchester Fungal Infection at the University of Manchester. The post is available
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. The lab is located in the Manchester Institute of Biotechnology (MIB), a unique cross-disciplinary research institute at the University of Manchester, which brings together more than 450 researchers with
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and materials engineering. They will do this by integrating modern data-centric approaches, such as physics-informed machine learning, structure-aware modelling, and digital-twin methodologies, with