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work on both probabilistic modeling, software development, and cancer biology analysis for this position. PhD in computer science, computational biology, or related quantitative field. Strong oral and
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and statistical modeling for reliable analysis on spatial multiomic data. The candidate will work on both probabilistic modeling, software development, and cancer biology analysis for this position
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will join a team of probabilistic modellers and machine learning researchers developing new collaborative AI principles and methods. This is an exciting topic which inspires new problems in fundamental
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. Structured around four interconnected research strands—(Re)conceptualising, Understanding, Forecasting and Tackling—the Centre’s programme aims for far-reaching insights that transform global responses
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or a numerate discipline OR equivalent experience. Broad knowledge of probabilistic models, Bayesian inference and machine learning methods. Good knowledge of R, Python or both (links to project source
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at Trinity College Dublin (TCD) seeks to appoint an outstanding, enthusiastic, and highly motivated Research Fellow who will contribute to a project that uses machine-learning methods to forecast
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] Duties The appointees will assist the project leader in the research project - “Development of smart wellbeing-driven innovative forecasting technology (SWIFT) for mechanically ventilated environments
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impactful observation-based analyses informing forecasting ocean and climate models. Meeting these challenges, within the European HORIZON EUROPE projects GEORGE (https://george-project.eu/ ) and TRICUSO
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interventions. The primary responsibilities include: (i) Extend and evaluate a Malaria Early Warning System (MEWS) across international borders, improving spatial and temporal forecasting; (ii) Investigate how
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around data science, econometrics and statistical modelling. For instance developing new probabilistic modelling tools to help government, researchers and communities better understand and anticipate