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are demonstrated knowledge related to acoustic modelling, measurement and soundscape. o Essential are demonstrated data analytic skills, ideally with machine learning or statistical modelling • Other general
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for drug discovery. Publishing peer-reviewed research and contributing to industrial software tools. About You To be successful in this role, you will have: A PhD in machine learning, computer science
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unique combined system using an optimised AF scanning procedure that integrates Raman measurements to analyse lymph node biopsies within 10 minutes and machine learning algorithms to deliver quantitative
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and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre at the Nottingham Breast
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novel biomarkers by integrating proteomics, metabolomics, and genomics / transcriptomics data with machine learning techniques. The position is to be filled starting November 1, 2025, either full-time or
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Operations & Technology Knowledge Center, with the following conditions: MAIN FIELD:………..…………………………………………………………………………………………… Management, with particular focus on the intersection of: Machine Learning Causal
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integration and AI models tailored for fish behaviour, health, and stress signal analysis. Investigate and apply novel machine learning and deep learning techniques for pattern recognition, classification, and
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Tool (SWAT model), and/or Noah Land Surface Model with Multi-Parameterization Options (Noah-MP model). Experience in either developing or applying Artificial Intelligence and Machine Learning tools and
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postgraduate degree, ideally a PhD, in statistics, machine learning, or a related field. Experience of developing new statistical methods and a strong working knowledge of a statistical software package, such as
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genome editing, CRISPRa/i Animal work and rodent surgeries Machine learning / artificial intelligence (using imaging or 'omics data) Responsibilities: Lead independent and collaborative projects; establish