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pathways, whilst their omission can introduce significant systematic biases in parameter estimation, detection pipelines, and tests of fundamental physics. In this PhD project, you will develop a
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Deadline: All year round How to apply: https://uom.link/pgr-apply UK only This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual tax-free
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* Theoretical foundations of machine learning The group has strong ties with the Centre for Discrete Mathematics and its Applications (DIMAP), established in 2007 jointly with Warwick Mathematics Institute and
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click the 'Apply' button above, create your account, and use the link sent by email to start the application process. During the application process please select the PhD in Mathematics. *Important notes
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cell and spectroscopic analysers. Programming (e.g., R, Python) and machine learning for advanced atmospheric time-series analyses. Skills for presenting research at conferences and writing peer-reviewed
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The construction industry accounts for 8–10% of global anthropogenic CO₂ emissions and faces significant challenges in achieving NetZero targets by 2050. This PhD project offers an exciting
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Qualification type: PhD Location: Essex Funding for: UK Students, EU Students, International Students Funding amount: UK tuition fees and a standard tax-free stipend for three years equivalent
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easier to detect and measured experimentally. However, it is not well known yet how this process emerges and how one can control it. This PhD project will focus on developing the necessary theoretical
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for computer, lab, and fieldwork costs necessary for you to conduct your research. There is also a conference budget of £2,000 and individual Training Budget of £1,000 for specialist training Project Aims and
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are processed in burned soils is crucial for predicting environmental impacts and informing effective wildfire management. The PhD student on this project will investigate how microbial communities mediate