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spatial data of ecosystems and human activities, and more holistic analyses of socio-ecosystems. Your will collaborate with colleagues and stakeholders and contribute to scientific reports and publications
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benefit sharing. The candidate will work on several case studies, including a case study in Northern Kenya in collaboration with the Wyss Academy for Nature (University of Bern). Your job Despite the
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excellent facilities, collaborates closely with local universities and non-university research institutions, and is a founding member of the German Center for Infection Research (DZIF) and the Centre
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activity, oxygen storage capacity), in collaboration with machine learning experts to build predictive models. Producing well-characterized nanoparticle batches for external testing and catalytic
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at the Division of Fluid Dynamics, within the Department of Mechanics and Maritime Sciences at Chalmers. The project is carried out in collaboration with Vattenfall Research and Development, and is part of
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desirable but learning can be completed during the PhD. Excellent communication and interpersonal skills to facilitate collaboration within interdisciplinary research teams. Application Process: To apply
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desirable but learning can be completed during the PhD. Excellent communication and interpersonal skills to facilitate collaboration within interdisciplinary research teams. Application Process: To apply
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
. CDDE provides access to advanced simulation tools and a collaborative environment focused on AI, digital twins, and immersive technologies. This project is co-sponsored by Rolls-Royce, offering unique
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
in machine learning methods for pattern recognition and prediction. An academic or practical background in sleep science and/or elite sport is highly desirable. The candidate will be embedded within