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. The programme offers postgraduates the opportunity to undertake a 4-year PhD research project whilst enhancing professional development and research skills through a comprehensive training programme. You will
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, temperature, CO2) conditions from pole-to-pole. This work will be done at UEA. Training The PhD candidate will acquire skills from the bench (e.g., PCR, cloning, phenotyping) to bioinformatics (e.g., Phython
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atmosphere (1). Research Methodology: The primary objective of this PhD studentship is to develop near real-time capability for top-down ffCO2 quantification, based on synchronous changes in atmospheric CO2
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Applications are invited for three (3) PhD Studentships, based at the Department of Statistical Science, UCL. The positions can involve any topic within the Statistical Science remit. The positions
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skills (Python preferred) and solid understanding of machine learning and deep learning, including computer vision techniques. Ability to read, write, and communicate scientific texts clearly; strong
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-disciplinary PhD project aims to provide a clear picture of the landscape of battery manufacturing, waste and end-of-life processing. The project aims are to: Identify waste streams and energy requirements
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Primary Supervisor: Dr Zoja Vukmanovic Scientific background: Layered intrusions represent natural laboratories frozen in time that provide us an opportunity to study how magma cools and differentiates, and how precious metals concentrate to form ore deposits. The ore deposits found in these...
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Primary Supervisor - Prof Tracey Chapman Strong interdisciplinary training, within the ARIES Ecology and Biodiversity theme, to equip you with high-in-demand analytical skills in phenotypic and molecular genetic engineering. Scientific Background In all species that lay eggs externally - in...
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Electrical and Electronic Engineering Department, Imperial College London PhD Studentship in Damping of IBR-induced Oscillation Position Summary: Applications are invited for a PhD studentship, to
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trust in digital communications and readily bypass conventional security controls. This PhD research proposes to design, develop, and validate a novel, explainable, multi-modal detection framework. By