58 phd-studenship-in-computer-vision-and-machine-learning PhD positions at University of Birmingham
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, few people are trained in its operation. This PhD project will involve training on, and the further development of native mass spectrometry technology. The student will operate within the Advanced Mass
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enable by two-photon polymerisation 3D printing rationalizes the use of the powerful topological optimisation. The PhD candidate should have completed (or about to complete) their undergraduate degree in
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Fossil tracks and trackways (a type of trace fossil or ichnofossil) provide highly complementary information to the body fossil record. Tracks are more abundant than body fossils as organisms have one skeleton, but may leave many of tracks in their lifetime, often occur in stratigraphic levels...
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-partnership MIBTP Programme Code for this project: 167D PhD Biosciences FT (MIBTP) How to apply: To apply, please click on the 'Apply' button above, make an account, and submit an application via the university
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elucidate novel interactions within critical signalling pathways and increase our understanding of signal transduction regulation of fundamental cellular processes. Funding notes: This is a PhD studentship
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and spatial resolution, to make a leap in this field. The PhD research programme will squarely address these challenges. The PhD candidate should have completed (or about to complete
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of Sentinel-2 fluvial scenes’. Earth Surf. Process. Landforms, 45, 3120–3140. Carbonneau et al 2020) ‘Adopting deep learning methods for airborne RGB fluvial scene classification’. Remote Sensing of Environment
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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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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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We invite applications for a fully funded PhD studentship (3.5 years) hosted by the University of Birmingham and conducted in collaboration with Siemens and the UK Met Office. This project is ideal