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Field
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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biology, chemistry, psychology and social science, facilitating knowledge discovery. The intuitively uninterpretable high-dimensional data and network data become visually scrutable upon being mapped into 2
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nature of this project, please contact Prof. Tony McNally (T.McNally@warwick.ac.uk ) directly for further information. Essential and Desirable Criteria: 1 or 2.1 degree in chemistry, chemical engineering
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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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ballot may leak the voter’s preferences if published publicly in plaintext, as the ranking order can reveal detailed information about the voter’s identity. Therefore encryption is necessary to hide
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, or physics, and will demonstrate a willingness for experimental fieldwork and data analysis. This PhD offers a unique opportunity to contribute to frontier research in atmospheric chemistry, with
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health, and intelligent operations. It is particularly suited to candidates with academic backgrounds in Industrial Engineering, Aerospace Engineering, Management Science, Operations Research, Transport
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This fully-funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA), Cranfield University and Spirent Communications, offers a bursary of £25,000 per annum, covering full