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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
investigate the large area production of graphene, BN, MoS2 and other layered materials, optimize their transfer process in view of their application in energy, electronics and photonics. This will include
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the analysis of the complex data and cellular models (Big Data and Kavli Institutes). The DPhil will provide the student with multidisciplinary skills including specialized training in bioinformatics, genetic
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problems in health data science. Air pollution is composed of several different environmental pollutants, for example particulate matter (PM10 and PM2.5), ozone (O3), nitrogen dioxide (NO2) and sulphur
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, including: Genomic technologies – hands-on experience in long-read sequencing and variant interpretation Bioinformatics – pipeline development, visualisation, and statistical modelling PRS – applying big data
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-impact questions in environmental economics and labour economics. Key responsibilities for this role includes: Data collection, cleaning, and merging from very large-scale microdata sources (e.g., terabyte
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, interdisciplinary research. Our department remains at the forefront of engineering innovation, delivering sustainable solutions with global impact. As a large, multi-specialisation department, we thrive
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models, alongside complex drug screening, efficacy
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Fully funded positions available to start in 2025 or early 2026 Projects span plant genetics, climate-resilient breeding, AI and data science, soil health, sustainable agriculture, circular economy
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will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show challenging properties of uncertainty, irregularity and