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optimization; bioprospecting for novel microbial hosts, enzymes, and metabolites to support sustainable biomanufacturing. (Bio)pharmaceuticals: Processing science and technology for bio- and chemical
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specific behaviours, analysing and interpreting imaging data to support neuroscience research objectives, collaborating with interdisciplinary teams to develop and optimize imaging protocols, and performing
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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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an integrated model of plant carbon allocation, based on eco-evolutionary optimality theory. The PDRA will be explicitly responsible for designing an approach to evaluate and model carbon allocation to non
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Python, using GPUs), with the precise balance determined by the candidate’s background and interests. The mathematical tools involved will include matrix analysis, optimization, backward error analysis
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. The research focus of our group is on parallel computing, supercomputing, and performance tuning and optimization of advanced applications. Our team currently consists of 10 scientific and 3 administrative
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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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). 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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. AI-driven technology to achieve optimal performance Integrate developed PA techniques into practical active antenna array demonstrators. Conduct experiment with existing USRP platform for wireless end
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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