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biology experience with laboratory-based research (e.g., cell culturing, molecular techniques, bioinformatics, flow cytometry) ability to work independently and as part of a research team strong analytical
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biosynthetic machinery Applying novel GAG analytical technologies to investigate how changes in GAG structure and organisation drive and/or respond to shifting developmental stages. Working Environment: Based
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to enable discoveries that improve people’s lives. Its 20-year vision is for large-scale data and advanced analytics to benefit every patient interaction, clinical trial, and biomedical discovery and to
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project will involve collecting and analysing EEG, fNIRS and home wearable recordings from babies and children. Experience of advanced data analytics, including if possible experience of coding in Matlab
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, fNIRS and home wearable recordings from babies and children. Experience of advanced data analytics, including if possible experience of coding in Matlab and/or Python, is highly desirable. Experience
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experience of data science analytical packages and R or Python would be advantageous. Funding The project is funded by the UKHSA and Nottingham University Business School. As a UK public body, UKHSA can only
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, microbiology, environmental science, chemistry, physics or data science. Applications would be keen to blend hands‑on experimentation with advanced analytics to create low‑carbon, nature‑based solutions
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, while simulations are subject to error due to uncertainty in nuclear data and unresolved physical processes e.g. thermal expansion and fine-scale inhomogeneities. Generating independent simulation
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, deposition and characterisation tools, including bespoke burner-rig testing design for realistic thermal testing. Combination of experimental, analytical, and modelling training, ideal for interdisciplinary
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show