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Field
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with Bayesian/ML methods is a plus Proactive, collaborative communicator with sound statistics, problem‑solving skills, and a commitment to research integrity and open, reproducible science We offer
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strategies to mitigate impacts on adjacent waters. Research activities include: coordinating with multiple stakeholders and collaborators to define objectives and research questions; leading participatory co
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spectroscopy will track the autodetachment to internal conversion and dissociative electron attachment products in real-time. Key responsibilities: To understand and convey material of a specialist or highly
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, rental platforms, and production systems—where decision-making must balance conflicting objectives, leverage real-time data, and ultimately support sustainable profitability. Examples include optimizing
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In this role, you will be responsible of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with
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- identifying which measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make
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methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon
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to implement advanced computational pipelines, including machine learning, deep learning, Bayesian inference, and probabilistic mixed membership modeling for innovative research. · Contribute
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of data matrices (using parsimony and Bayesian phylogenetics); - Conducting multivariate analyses using R. LanguagesENGLISHLevelExcellent Research FieldBiological sciencesEnvironmental science » Earth
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of London Cancer Institute. Objectives: The aim of the project is to study chromatin remodeling defects in cancer. The successful candidate will be responsible for designing and executing experiments