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optimisation and machine learning code, understand transportation modelling approaches, read and digest literature on the topic and write academic papers. Essential requirements: PhD or equivalent qualification
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available from 01/04/2024 to 31/03/2025. The successful applicant will combine remotely sensed datasets with machine learning to map peat extents, habitats, habitat condition and change. The post will include
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machine learning in relation to neurodevelopment in collaboration with the Complex Disease Epigenomics group (led by Prof. Jonathan Mill) and the MRC Integrative Epidemiology Unit at the University
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understanding. The successful candidates will be responsible for conducting cutting-edge research in machine learning, multimodal data analysis, and video understanding applied to social media data
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possess a relevant PhD or equivalent qualification/experience in maths, physics, computer-science, meteorology, or a related numerate scientific discipline. The successful applicant will be a nationally
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funding and contribute to the process of securing funds and make presentations at conferences and other events. Applicants will possess a relevant PhD or equivalent qualification/experience in a related
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the field of applied quantum algorithms and quantum computing. We welcome the applicants with background in various research subjects, including but not limited to quantum optics, groups and algebras, machine