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service’s Points Based System. Therefore, BU will not be able to sponsor individuals who require permission to work to carry out this position. For more information, please visit https://www.gov.uk/skilled
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. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus. You will join an interdisciplinary team of researchers spanning imaging science, machine learning
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multimodal satellite Earth Observation and machine learning can be used to quantify cyclone and storm damage in plantation forests. The core focus could be on integrating pre-storm LiDAR with post-storm
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facilitate active scientific exchange and foster a good atmosphere, and therefore play a big role in our team. Learn more about us here: https://swa.cs.univie.ac.at/ Your future tasks: You actively participate
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construction as it relates to manufacturing? And are you thriving on theory-driven and empirically-validated research excellence, learning and teaching with and for engineering leaders of the future? We’d love
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. The overarching aim of the project is to use machine learning methods to understand why many people who are referred for treatment will drop out prematurely. To do this, two studies are planned. One will use a
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experiments for investigating the neural mechanisms underlying habitual behaviours and learning adaptation to uncertainty. You will use fMRI and neurostimulatory techniques (ultrasound neurostimulation and/or
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that can be run. Emulating expensive processes could allow more data to be generated from better models, at lower cost. The central science question is: how can machine learning and evolutionary computation
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research directions include: Develop a novel microenvironment classification algorithm by extending existing methods Model indoor air quality levels in London microenvironments by combining machine learning
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escalation point for security incidents, resident, car park and parking issues and queries as well as faults to security systems and equipment including car park barriers, CCTV and intruder alarm systems