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Laboratory techniques for sample preparation Analysis of mass spectrometric datasets and statistical calculations Contribute to in vitro analyses Contribute to carrying out animal experiments Contribute
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the right one for you! This is a fully funded PhD position to develop micromechanical models of high-pressure die-cast aluminium, a unique opportunity for a motivated individual to work in a collaborative
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-to-have: Work experience in simulations with proteins/membranes and their analysis Good communication and interpersonal skills Motivation and a collaborative mindset What we provide to you: Open access
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studies to aid in the experiment design, impact analysis and icing code droplet impact solver refinement. The main impact of the work will be to provide droplet impact data and analysis at high speeds which
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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Responsibilities for the role include: Data collection, cleaning, and merging from large-scale microdata sources (e.g., patents, dissertations, bibliometrics). Conduct data analysis using econometric and statistical
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community engagement. In this role, you will: Contribute to research on ecological and spatial data for urban environments: Conducting fieldwork, data collection and analysis related to urban air quality and
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Status: Closed Applications open: 15/05/2025 Applications close: 31/05/2025 View printable version [.pdf] About this scholarship Description/Applicant information This scholarship is funded as part
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status, and nursery layout. Your Role: As our PhD student, you’ll be at the forefront of developing smarter solutions, working in partnership with UK Health Security Agency (UKHSA). You'll use
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: - participate in knowledge mobilization - Literature reviews and data analysis for TRANSFORM research project - Participate in regular project meetings on planning and research generation Qualifications