275 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"SciLifeLab"-"IFM" positions at University of Sheffield
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Airyscan, spinning disk) and analysis. Contribute to lab organisation including ordering, cleaning, training, supervision. Critically analyse data and experimental design. Presentation of results in the form
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of programme level approach in the School and contributing to the strategic development of the portfolio. This will involve coordinating high quality and consistent programme and module information in various
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subjected to a typical loading scenario. This research will benefit from excellent computing facilities, expertise in computer-aided engineering (CA2M lab), the available experimental facilities including
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experimental manufacturing data. Thermoplastic overmoulding is an advanced composites manufacturing process combining stamp forming of aligned, continuous fibre composites (CFCs) and injection moulding
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of the UK’s most distinctive university campuses safe, operational, resilient and compliant. From the iconic Grade II listed Arts Tower to the state-of-the-art Information Commons, you’ll be working with a wide
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delegated budget responsibility for individual events. Analyse data and feedback from events, creating reports and making recommendations for future activity. Act as a key point of contact for event enquiries
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neurons using our in-house small molecule approach. Ordering and preparing reagents for the lab to run efficiently. Maintain accurate records of data. Assist PhD students / Research Associates with
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taking bookings (internal and external), capturing all meeting room requirements are stated, and ensuring that all meeting rooms are presentable at all times. Record and report visitor information
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and Environmental Science undergraduate programmes, and our new Masters in Environmental Science and Data. We particularly seek individuals with a proven track record in handling large-scale
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research directions include (but are not limited to): Data-Driven Material Characterization: Leveraging machine learning to extract constitutive models and material properties from experimental data and