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Applications are invited for an AstraZeneca Non-Clinical PhD Studentship in Development of an Integrated Pre-Clinical Pipeline for Safety Assessment of Small Molecule and Peptide-Based
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Electric motors and the systems they drive consume half of global electricity. These systems are typically very inefficient and contribute to a significant amount of energy wasted. By physically integrating power electronic converters and electrical machines we can use common structures and...
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PhD studentship: Discovery of rational therapeutic biomarkers in breast cancer by systems pathology and deep learning Supervisor: Dr Hamid Raza Ali Department/location:Cancer Research UK Cambridge
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for work, money and society. This PhD combines economics, psychology and health science to look into this topic for the first time. You will gain skills in behavioural experiments, data science and health
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protection benefits provided by restored saltmarshes. The successful PhD candidate will work with laboratory experiments and develop numerical and AI models capable of supporting coastal management and
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From electric vehicles to grid-scale energy storage, the future of clean energy relies on breakthroughs in battery technology. This PhD will develop cutting-edge terahertz spectroscopy methods
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Application deadline: All year round This 3.5-year PhD project is fully funded; students who are eligible to pay tuition fees at the Home rate are eligible to apply (more details can be found here
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and machine learning methodology to help deal with key challenges in developing such models in large-scale observational electronic healthcare record data. These models will be applied to important real
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technologies is therefore essential to support a sustainable and resilient battery supply chain. This PhD project, in the Energy Materials Group, at the University of Birmingham, will investigate advanced direct
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This PhD asks a different question: instead of demanding more data, can we build language models that learn smarter from less? You will design AI architectures that adapt to the structure of a