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2021 to maintain biodiversity net gain while enabling growth. These necessary regulations demand a rapid response from industry to assess the impact of production processes on biodiversity. However, we
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This PhD project is at the intersection of electromagnetism, numerical methods, and high-performance parallel computing, with application towards the design and optimisation of integrated circuits
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death. The role of NLR genes in these processes has been thoroughly described for plants and animals, but how they contribute to the fungal immune system is unexplored. Fungal NLR genes also show hugely
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, few people are trained in its operation. This PhD project will involve training on, and the further development of native mass spectrometry technology. The student will operate within the Advanced Mass
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parallel expansion in mining to meet this demand is expected. The environmental, economic and social impacts of this global expansion are significant and need to be assessed, so that we do not trade one
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tested by isothermal titration calorimetry (ITC) or microscale thermophoresis (MST) in collaboration with the lab of Prof. Andy Lovering. In parallel, minibinder/effector pairs will be co-expressed using
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applications. The research will examine how key parameters—such as printing speed, toolpath strategy, material rheology, and geometric complexity—influence interlayer adhesion. In parallel, the project will
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self-motivated in keeping to project deadlines Ability to work on several tasks in parallel and to manage competing demands Understanding of equal opportunity issues as they may impact on areas
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candidate with a strong quantitative background (e.g., in computer science, statistics, bioinformatics). The following skills are essential for this project: Excellent programming skills in Python. Proven
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of bioinformatic analysis of microbial genomics data High level analytical capability Ability to communicate complex information clearly Contribute to the planning and organising of the research programme and/or