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Mary University of London. About You Essential requirements for this post include a BSc or equivalent in a biological science or allied health field. A MSc in Cancer Biology, Pathology, Cancer
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or computational biology, or equivalent, with a sound knowledge of cancer genomics and omics techniques. They will have experience in hands-on analytic skills and knowledge in analysing a large range of omics data
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Department: School of Engineering and Materials Science Salary: £40,223 - £47,178 per annum (Grade 4) Reference: 2637 Location: Mile End Date posted: 12 June 2024 Closing date: 4 July 2024 Further details and apply Overview About the Role We have an exciting opportunity for an individual to join...
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out there about vital subjects such as cancer biology, pharmacy, pharmaceutics, sport and nutrition, but it is the real world application of these areas of study that really makes our school stand out
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or computational biology, or equivalent, with a sound knowledge of cancer genomics and omics techniques. They will have experience in hands-on analytic skills and knowledge in analysing a large range of omics data
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biology and cell biology would be welcomed. The successful candidate requires a PhD degree in a biological or medical sciences discipline, with a good track record in publishing their work in leading
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Over the last 10 years, genome wide association studies (GWAS), exome sequencing and short-read genomic sequencing have enabled a revolution in our understanding of the genetic basis of neurodegenerative diseases, their progression and disease pathways. In this period, most of the Mendelian...
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the operations of our newly-created, state-of-the-art Chemistry, Biology, Physics, and Design laboratories, as well as our dedicated maker space, on the University campus. The successful candidate will recruit and
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join the Biology Department and will integrate into a dynamic academic team, striving to modernise our delivery of educational activities. We are a dedicated and collaborative department that supports
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limited for 3 years. About us: We develop novel methodology for data analysis at the cutting edge of applications in (cell) biology. In doing so, we closely collaborate with lab scientists and benefit from