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energy planning. This involves exploring how advanced data on nature and biodiversity (derived from AI-supported monitoring and analysis of sources such as satellite imagery, acoustic sensors, and camera
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(e.g. safety, norms, networks) influence active lifestyles; develop and test physical activity and destination choice models, integrating data from sources such as sensors, surveys, Google Street View
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(derived from AI-supported monitoring and analysis of sources such as satellite imagery, acoustic sensors, and camera traps) can inform spatial planning and decision-making for solar and wind energy
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choice models, integrating data from sources such as sensors, surveys, Google Street View imagery, and microdata (e.g. CBS Lifestyle Monitor, ODIN); use computational and AI-based modelling approaches
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; validating models using existing offshore datasets, lab-scale experiments, and collaborating with ongoing projects; developing optimisation algorithms for ensuring techno-economic feasibility of FPV systems
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inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable