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it will also involve a small degree of teaching and supervision. To that end, the successful applicant will be expected to take part in the department’s teaching and supervision activities and to teach
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. Candidate will have the opportunity to investigate human Tregs in vitro and in vivo, learning from patient samples and humanized mouse models, implement state-of-the-art technologies such as functional
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(KCL, London, UK) but will also have the opportunity to travel and work at the Centre for AI and Machine Learning (ECU, Perth, AU) and the School of Psychiatry and Clinical Neuroscience (UWA, Perth, AU
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Employment 1.0 FTE Gross monthly salary € 3,546 - € 5,538 Required background PhD Organizational unit Faculty of Science Application deadline 12 October 2025 Apply now Are you a scientist with a PhD
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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Commensurate with experience Type of Position Student Position Time Status Full-Time Required Education PhD Required Related Experience Experience in life science or related disciplines. Required License
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on the physical layer design of wireless communication systems and explore enabling technologies for 6G and beyond wireless networks. Applicants must hold a PhD degree in electrical/electronics engineering
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. For this multidisciplinary project, we are looking for a highly motivated cell biologist who holds a PhD in a relevant field with a commensurate publication record. We welcome applications from candidates with a background in
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community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals