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models and algorithms, particularly within Bayesian, generative, or probabilistic machine learning frameworks, together with deep knowledge of causal inference, prognostic modelling, and individualized
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. They will have experience working with bioacoustic and camera trap data and be familiar with deep learning methods, with a proven track record of training and applying audio signal classifiers. The successful
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An exciting opportunity has arisen for a Postdoctoral Research Assistant in the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres
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volcanic arc using state-of-the-art deep learning techniques and modern seismological processing workflows, reporting to Dr Sacha Lapins. This role offers an exciting opportunity to process multi-year
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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the form of papers, posters or oral presentations Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow Downloading a copy of our Job Description Full details
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the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres of technology, economy and our everyday life. Machines perform comparably to, or even surpass
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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models when faced with data drift, bias, and fairness challenges. The research will involve developing deep learning and synthetic data generation approaches and applying them to exemplar studies in
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supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning