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Field
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, sustainability science, geography, or a related field. You have experience with quantitative research methodologies, including mathematical programming or scenario modelling. You have experience with spatial
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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sound like you? You should hold a Master's degree in spatial planning, urban and regional studies, policy and systems analysis, strategy and decision-making, infrastructure management and operations, or a
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2026. The UNFoLD lab specialises in the experimental measurements, analysis, and modelling of unsteady vortex-dominated flow phenomena, with applications in bio-inspired propulsion, wind turbine rotor
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. This knowledge will support the designation of marine protected areas in line with the “30 by 30” conservation target. A central component of the project is the integration and analysis of diverse data sources
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changing spatial regulations. You will also help design economic decision-support tools to inform more inclusive and evidence-based marine policy. Your duties and responsibilities include: analyzing
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support to competent authorities on how to include shipping pressures and impacts in marine environmental management and spatial planning. Research environment Our research aims at supporting sustainable
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exposome and dynamic exposome modeling, learning in timeseries and spatial data, and hybrid deep learning-causal modeling. The successful applicant should have significant research experience in at least two
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emerging types of national emergencies and evaluate their spatial and operational implications. This will include an analysis of UK population distributions, terrain, infrastructure access, and airspace
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application-oriented research that unlocks the potential of data through rigorous analysis – advancing solutions in societally relevant domains. Your profile Master’s degree in Statistics, Industrial