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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
illnesses. The post holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning
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research is essential, and experience working with electronic health records, microbiology, or machine learning would be very welcome. Applications from candidates who do not fulfil the essential criteria
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), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a PhD (or be near completion) in a field such as AI, computer science, signal
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postgraduate-level research in Computer Science, Cybersecurity, Information Security, Information Technology, Artificial Intelligence, Machine Learning, or a related field, have experience with securing AI
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influence clinical practice. We welcome applications from candidates with following backgrounds: Candidates with strong experience in medical image analysis, machine learning (especially deep learning) and
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will provide guidance to less experienced members of the research group, including postdocs, research assistants, technicians, and PhD and project students. Key responsibilities: • Manage own
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regenerative medicine, biosensing, and therapeutics. Learn more at www.stevensgroup.org . This post is available from October 2025 for a fixed-term of 18 months, with the possibility of part-time appointments
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programming), (2) populating agent-based models with realistic agent behaviours (e.g. using machine learning techniques), (3) calibrating large-scale agent-based models and (4) validation and verification
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. Selection criteria: • Hold, or be near to completion of, a PhD/DPhil in biomaterials, bioengineering, biology, chemistry, nanotechnology, or related field • Experience establishing and
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opportunity to teach. Applicants should hold, or be close to completing, a PhD in plasma physics or high-power laser-plasma interactions. They should have extensive experience of working with particle-in-cell