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Adopter programmes, where appropriate. We are looking for an enthusiastic, motivated graduate in (health) Data Science, Computer Science or related field who is interested in the deployment, user acceptance
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products to be used in plants. Lead the project and plan own workload Publishing scientific papers. Presenting work and results to both the KTP supervision team and at scientific meetings. Ultimately deliver
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to develop and validate paediatric bone models through a combined computational and experimental approach, in collaboration with clinical partners at the Sheffield Children’s Hospital. The ideal candidate will
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higher education (HE) institution, except for anyone who has participated in the Work Programme. You may still be eligible if the apprenticeship will allow you to acquire substantive new skills and there
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/MSc or equivalent in Computer Science or Software Engineering (assessed at: application/interview). A track record in software testing, testing for autonomous systems, or autonomous driving system
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diseases, combining biomechanical experiments, micro-Computed Tomography imaging, Digital Volume Correlation, and Nanoindentation. The position is funded as part of the project “ChildBone: A novel digital
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Neutron total scattering (Pair Distribution Function analysis), as well as scanning and transmission electron microscopy (SEM & TEM). Main duties and responsibilities Undertake the programme of work and
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A search for pharmacological inhibitors of a cancer-associated adhesion GPCR in the zebrafish embryo
support will be provided throughout via an interdisciplinary supervisory team and an established Advisory Programme. The student will join the well-funded and friendly Whitfield lab (see blog). The varied
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the ability to design a programme of research that will produce high quality outputs and have real impact in academia and beyond. As an equal opportunities employer, we particularly welcome applications from
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late July or early August. This will consist of interview and lab tour at the University of Sheffield for short listed candidates. We plan to let candidates know if they have progressed to the selection