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-edge research in machine learning and automated reasoning for safe algorithmic systems. The Research Fellow will be responsible for developing advanced theory and machine learning algorithms
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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-leading database of MRI images of childhood tumours and have developed AI approaches to diagnose different types of tumour. To be useful for patients, this needs to be delivered in hospitals in real time
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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below. Develop research objectives and proposals for own or joint research, with assistance of a mentor if required Contribute to writing bids for research funding Analyse and interpret data Apply
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co-benefits and public acceptability of transport decarbonisation interventions. The role involves both quantitative and qualitative research to: Develop frameworks and metrics to assess the health
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and management of IM. The success of this project will provide sufficient evidence to develop a novel antimicrobial treatment for GIM, which could prevent the development of GAC. Role Summary Work
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holder will play a key role in supporting quantitative data analysis, including the development of statistical analysis plans, and interpretation in a cluster trial setting. There are also opportunities
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sales, IP generated) and/or public understanding of the discipline or similar Main Duties The responsibilities may include some but not all of the responsibilities outlined below. Develop research