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Field
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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programming and data analysis. Interest in developing methods, algorithms or software. Evidence of publications in high-quality peer-reviewed journals. Excellent communication skills. Experience
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algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. This will be done by combining the mathematical and computational cultures
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or use existing simulation platforms to validate the developed algorithms and models. Analyse simulation data, and create visualizations to support research findings. Design and build prototypes
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highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which
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binding pockets. About the role We are seeking a highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to identify domain functional families
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-fostering prototypes through co-design with children, creating evaluation frameworks to assess children's algorithmic agency in educational contexts, and establishing design principles that prioritize
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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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their own research programme as well as support in the delivery of AI upskilling and expertise transfer to government. What you would be doing The objectives for the role are: to deliver ground-breaking