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robust, reproducible genomic bioinformatics pipelines, using modern workflow systems and high‑performance computing platforms. Produce rigorous, high‑quality research outputs that advance applied genomic
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robust, reproducible genomic bioinformatics pipelines, using modern workflow systems and high‑performance computing platforms. Produce rigorous, high‑quality research outputs that advance applied genomic
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discipline. You will have demonstratable experience in field-based research, microbiology (field and laboratory), bioinformatics (e.g. metagenomics and high-performance computing), and handling plants and soil
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from AI data centres and high-performance computing. The appointed Research Associate/Fellow will conduct computational studies of electronic transport and quantum phenomena in 2D semiconductor materials
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statistics. Software frameworks: Excellent programming skills in Python, R or similar, with experience in frameworks such as PyTorch, TensorFlow, JAX, etc. HPC & Big Data: Proficiency in high-performance
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) to join an interdisciplinary research programme addressing challenges associated with the analysis, monitoring, and improvement of complex engineering systems, with applications in energy and infrastructure
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imaging programme which includes high resolution functional imaging studies; simultaneous EEG-fMRI studies of infant learning; the development of novel MR imaging methods on a portable ultra-low field
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working with Johnson Matthey, but aligned with the EPSRC funded Programme Grant “Dialling up performance for on demand manufacturing” (EPSRC reference: EP/W017032/1). Our vision is to create a toolkit and
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(field and laboratory), bioinformatics (e.g. metagenomics and high-performance computing), and handling plants and soil, particularly roots (i.e. rhizosphere collection and root traits). You will have a
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(field and laboratory), bioinformatics (e.g. metagenomics and high-performance computing), and handling plants and soil, particularly roots (i.e. rhizosphere collection and root traits). You will have a