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integration or multi-modal data, Ability to work with and develop interfaces for complex or hybrid sensing systems. Excellent interdisciplinary communication – Strong collaborative skills to work effectively
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research projects, providing qualitative and mixed methods process evaluations. This is an exciting opportunity for someone who is on their way to becoming an independent researcher as there will be scope
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complex patient pathways. The project will consist of three studies: Mapping and modelling of interaction patterns in different patient pathways (e.g. stroke, cancer, elderly care). The objective is to map
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cleaning products. This role is part of the Supergen Bioenergy Impact Hub, a multi-institutional initiative funded by UKRI to support innovation and impact in the UK bioenergy sector. The candidate will work
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About Trinity: Trinity is Ireland’s leading university and is ranked 75th in the world (QS World University Rankings 2025). Founded in 1592, the University is steeped in history with a reputation
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Salary: Full time starting salary is normally in the range £36,130 to £45,413 with potential progression once in post to £48,149 Contract Type: Fixed Term contract up to March 2028 Background
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- Location: Wallumattagal Campus, North Ryde About the Role This position is part of the John Templeton Foundation’s project Cognition All the Way Up. The appointee will work with Dr Bourrat (Philosophy), Prof
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
for this position lie at the intersection of philosophy of biology and philosophy of cognitive sciences. About Us Macquarie is a university engaged with the real and often complex problems and opportunities
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, quantitative psychology or a related field at the time of appointment. Experience working with complex survey data. Highly proficient in R, SAS, and/or STATA. Demonstrated ability to work in a highly
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and journals. You will be expected to: Conduct cutting-edge research in: Multi-Agent Systems (MAS) for complex, dynamic, and uncertain environments. Multi-Agent Reinforcement Learning (MARL), including