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the programme code: 8080F Research area: Statistics Select ‘PhD Mathematics (Full Time)' as the programme of study You will then need to provide the following information in the ‘Further Details’ section: A
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, or physics, and will demonstrate a willingness for experimental fieldwork and data analysis. This PhD offers a unique opportunity to contribute to frontier research in atmospheric chemistry, with
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, microbiology, environmental science, chemistry, physics or data science. Applications would be keen to blend hands‑on experimentation with advanced analytics to create low‑carbon, nature‑based solutions
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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. Development of DT information modelling, data fusion, and forecasting guidelines and standards, and technology maturity benchmarks to derive cloud platform maturity level standards. Lead on the development
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the PhD in Engineering programme. Make sure to reference the supervisor's name (Dr Farzad Hayati) in your application. Informal enquiries are welcome and should be directed to Dr Farzad Hayati at f.hayati
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PhD in a relevant discipline to the project: social science, anthropology, chemical or biomedical engineering Experience with qualitative research methods (e.g., ethnography, qualitative interviews
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the PhD has been awarded. Fixed-term: The funds for this post are available for 18 months in the first instance. To apply online for this vacancy and to view further information about the role, please
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the PhD. The Faculty has outstanding facilities and works in partnership with leading industrial partners. Please contact Mohammad Reza Ilkhani ezzmi1@exmail.nottingham.ac.uk for further information and an