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theoretical basis for modelling functional biodiversity, based on eco-evolutionary optimality (EEO) theory. The PDRA will be explicitly responsible for statistical analysis of plant trait data and the
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). The ideal candidate will have: A PhD in environmental science or closely related discipline by the start date of the appointment Broad understanding of eco-evolutionary optimality concepts and modelling
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to deliver industry-relevant tools that enable optimal design and operation of hydrogen technologies in real-world application. The successful candidate will work at the intersection of multi-disciplinary
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nanomaterial-nucleic acid hybrids for optimal device bio- and gas sensing, as well as for optoelectronic applications. About You The candidate will have experience in materials science research and ideally DNA
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nanomaterial-nucleic acid hybrids for optimal device bio- and gas sensing, as well as for optoelectronic applications. About You The candidate will have experience in materials science research and ideally DNA
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studies within the hydrogen research hub (HI-ACT) funded by EPSRC. The project seeks to deliver industry-relevant tools that enable optimal design and operation of hydrogen technologies in real-world
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optimizing their performance in high-energy-density applications. The coated LFP materials should exhibit superior mechanical and chemical resilience, ensuring that the coatings maintain their structural
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through long-term impact assessment and optimization. The goal is to develop a framework to estimate carbon emissions across AI's development, operation, and use. This framework enables stakeholders
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bottlenecks and optimization strategies. The digital twin will serve as a testbed for evaluating engineering trade-offs and guiding future hardware development. The appointed researcher will collaborate with
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challenge, making energy-efficient computing a critical research priority. This project addresses this challenge through a novel co-design approach that simultaneously optimizes both hardware and software