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, informed by the characteristics of the technology of delivery; • To validate profiles using available demand data; • To integrate barriers and enablers into the model of ASHP installation. Person
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., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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. BSc degree in Biology, Biomedicine or a relevant discipline (Biochemistry, Neuroscience) MSc degree (or equivalent) in Epidemiology, Biostatistics, Data Science or related discipline. Strong
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dissertation supervision. For this T&S role, you must have a PhD in a relevant subject (or a PhD near completion – i.e. strictly within three months of submission), and a strong scholarly profile or trajectory
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As a PhD student within the Economics Division, you will have access to a broad programme of research training opportunities. These include advanced methods courses, data skills workshops, and an
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breast cancer in animal models (4). In this PhD project, we will investigate: The effect of combined treatment with ITCs and a selected anti-cancer drug (sorafenib or triptolide) on breast cancer will be
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of good-quality data is typically limited for high-value critical assets. This PhD project will focus on developing, evaluating, and demonstrating physics-informed machine learning or domain knowledge
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information about the CDT, please visit the website or send an email to hello@fusion-engineering-cdt.ac.uk . The candidate should have a 1st / 2.1 class Undergraduate or Masters degree (or equivalent) in
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the wider PhD cohort in the group of meteorology and climate and the School of Geography, Earth, and Environmental Sciences. Supervisory team: Dr Gregor C. Leckebusch (University of Birmingham