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Field
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discrete choice modelling, behavioural data science or machine learning? Are you interested in developing the next generation of AI tools that accelerate scientific discovery while maintaining behavioural
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single-cell and single-nucleus multi-omics, machine learning/AI, computational biology, and experimental validation to understand cardiovascular disease progression and identify novel therapeutic targets
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and machine learning algorithms to analyse and interpret the acquired data. The successful candidate will work primarily with Dr Qimei Zhang in the Department of Engineering at the Nottingham Trent
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deep insight and interest in investigating the interaction between collaborative learning processes in specific knowledge domains in educational sciences and AI tools and infrastructures. Different types
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advanced statistical modelling, econometrics or machine learning with a particular focus on analysing large-scale behavioural data? Are you interested in developing new methodological approaches capable
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UiO/Anders Lien 16th October 2026 Languages English English English PhD Research Fellow in Machine Learning and Statistics Apply for this job See advertisement About the position Integreat
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or machine learning with a particular focus on analysing large-scale behavioural data? Are you interested in developing new methodological approaches capable of extracting behavioural insight from increasingly
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Intelligence & Machine Learning Develop machine learning and AI models to identify, predict and characterise genome instability patterns. Design generative and predictive computational models to infer mutational
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, data processing pipelines, machine learning and generative AI applied to physical activity and sleep research. The position will contribute to the development of an AI-based behaviour change tool and
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demonstrate experience in animal behaviour research, ideally in aquatic species, together with practical skills in video-based behavioural analysis and/or applying computer vision or machine learning methods