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responsibility of this position is to develop comprehensive machine learning and artificial intelligence (AI) pipelines for single- and multi-omics modelling and prediction. Working under PI supervision, the role
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. The aim of project is the safe integration of machine learning methods within the biopharmaceutical development process. This project offers an opportunity to be at the forefront of interdisciplinary
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have strong expertise in developing and implementing cutting-edge machine learning algorithms in Python and associated ML/AI libraries. Educated to PhD level, or near to completion, in (Health) Data
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. As systems and processes increasingly integrate machine learning components, whose behaviour can be unpredictable, ensuring their safety and alignment with expected outcomes is essential
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will also improve the efficiency with which P3s are detected with machine learning and will also explore alternative detection modalities, such as pupil dilation. More generally, the Research Fellow will
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. An intriguing possibility is that this variation could affect how children learn and perform in assessments. In this project, we will first establish how meaningful this variability is. We will address: How
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Magalhaes to support a research project aiming to develop machine learning methods for drug repurposing in ageing and frailty disease. We aim to employ a machine learning approach to predict, among existing
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University of Birmingham | Belfast International Airport, Northern Ireland | United Kingdom | 18 days ago
Specification A higher degree relevant to the discipline (usually PhD); Extensive teaching and scholarship experience at HE level within subject specialism; Proven ability to devise, advise on and manage learning
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disciplinary boundaries Strong analytical skills and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven
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-structure interaction and earthquake engineering Data-Driven Structural Engineering: Leveraging big data, machine learning, Digital twin and AI to enhance structural design, predictive maintenance, and