502 assistant-professor-computer-"https:"-"https:"-"https:"-"https:"-"EURAXESS" PhD positions in United Kingdom
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characterise novel genomic aberrations in up to 1000 paediatric cancer samples. Transcriptome sequencing, proteomic and metabolomic assays will help to understand the behaviour and consequence of the genomic
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Robotic-assisted surgery is rapidly expanding in the UK, with over 100,000 procedures performed in 2024 alone. Emerging 5G and future 6G networks are making remote surgery increasingly feasible
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their existing work in exploring possibilities for water reuse (see their recent repor t ). Results will help water companies and retailers understand the needs and concerns of key non-household customers in
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uncovering mechanisms that synchronize bacterial and plant circadian rhythms. Ultimately, this will help to better understand how soil microbes contribute to both crop nutrition and soil health. This PhD will
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of materials science, combining ab initio density-functional theory (DFT) calculations with novel ML methods. You will develop ML-assisted computational screening methods, building highly accurate models
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on Sunday 01 March 2026 Reference: PHD-DM-01 Project Title: Optimum strategies for UK beef producers to achieve net zero. Primary supervisor: Dr Daniel May Co supervisors: Professor Karl Brehendt
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that did not previously exist to help multiple research fields and world-leading national facilities and their user communities. You will also benefit from fantastic local communities in both Birmingham and
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facilities. The project will be supervised by Professor Chris Hardacre and Dr Marta Falkowska, with expertise spanning heterogeneous catalysis, reaction engineering, and neutron-based characterisation. Full
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help develop best practice and policy in applied conservation. It is not necessary for the candidate to have prior training in sociology or ecological methods as this will be provided on the programme
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‘Course Search’ to identify your programme of study: Search for the ‘Course Title’ using the programme code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ