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to be expert at all aspects – but instead hopefully versatile and willing to learn and expand their experience. Open to all: We run a diverse research group, supporting varied gender, ethnicity and
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learning. The post-holder will be familiar with the use of these techniques and experience of dataset construction and data mining will be essential. The successful applicant will have completed an MPhil/PhD
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, to the rigorous study of quantum many-body problems. The successful candidate is able to actively contribute to the research profile of the Faculty of Physics, teach courses (max. 4 hours/week per semester), and
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We are seeking a Postdoctoral Researcher in Human-AI interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Chris
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The University of Oxford is seeking a highly motivated Postdoctoral Scientist with expertise in biostatistics, machine learning, and cardiac magnetic resonance imaging (MRI) to join Professor Betty
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The University of Oxford is seeking a highly motivated Postdoctoral Scientist with expertise in biostatistics, machine learning, and cardiac magnetic resonance imaging (MRI) to join Professor Betty
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. The post is funded by the EPSRC’s Centre to Centre (C2C) Grant, “Mobile Robotic Inspector: Learning to Explore and Manipulate in the Real World” and is fixed-term of 24 months duration. The project will
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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design, delivery, and evaluation of a multi-school research study investigating the impact of mathematical storytelling on secondary students’ mathematics learning and related outcomes. Working closely
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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