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degree in statistics, computer science, data science or computational biology. Ideally, the applicant would have a background in both biology/biomedical sciences and statistics/data science. Applicants
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the above ‘Apply’ button. Under ‘campus’ please select *Loughborough* and select the programme ‘CDT Engineering Hydrogen Net Zero’. Please quote the advertised reference number *LU-EnerHy-2025-1* under
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This large-scale ecological project investigates the barriers and drivers of post-fire forest recovery. With climate change and the spread of forest fires to new areas, it is important to investigate the conditions that support forest recovery after a fire. The study areas can be defined using...
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English, you will need to meet the minimum English requirements for the programme, IELTS Academic score of 6.5 (with no less than 5.5 in each component test area) or equivalent. The studentship is supported
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wealth inequality, and how their career paths, values, and social networks maintain the status quo. As a PhD student on this programme, you’ll play a key role in generating new insights that could help
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Human Behaviour in projects targeting social good. Research at N/LAB focuses on the development and application of innovative computational methods using Big Data, Behavioural Science and Machine Learning
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to address the problem is to recruit a high performing PhD student to embark on a psycho-biological, mixed-methods programme of research that has the following aim: Develop a feasible, acceptable, efficacious
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of industrial cooking. The project will be based within the Centre for Sustainable Energy Use in Food Chains (CSEF) which has substantial expertise and experimental and computational facilities to support the
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cohort to benefit from peer-to-peer learning and transferable skills development. For full information about the programme, the research projects available and how to apply, please visit: http
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Computational Chemistry methods to model enzymes and polymers. Designing and optimising novel biodegradable polymers. Integrating novel AI tools into the discovery process for new polymer candidates. Project