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The Role The successful applicant will be responsible for the design, development, and implementation of deep learning and computer vision frameworks across a range of research projects
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Control engineering (experience with nonlinear systems is a plus) Machine learning and deep learning in context of physical systems Programming skills are required, with Python experience preferred. A good
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are comfortable navigating complex HPC environments and wrangling large datasets. You have experience with modelling through state-of-the-art machine and deep-learning methods and with hands
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areas of concerns to improve healthcare delivery to people with a learning disability and autistic people. We are contracted to deliver an annual report, regional reports and a number of deep dives as
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50 Faculty of Life Sciences Startdate: 01.08.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.07.2029 Reference no.: 4160 Explore and teach
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50 Faculty of Life Sciences Startdate: 01.05.2025 | Working hours: 20 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 30.04.2031 Reference no.: 3736 Explore and teach
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sufficient theoretical knowledge of deep learning-based methodologies as well as working with real-world data. Informal enquiries may be addressed to Prof Alison Noble (email: alison.noble@eng.ox.ac.uk
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industrial stakeholders, and we have ongoing collaborations with Fujifilm Diosynth, Opentrons, Lonza and Neochromsome. In collaboration with OccamBio Ltd, we aim at designing deep learning models to engineer
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analysis of PDEs (with deterministic and/or stochastic methods), Gaussian Random Fields, mathematical foundations of deep learning, functional analysis and measure theory. You can find more information about
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knowledge of methodologies such as deep and statistical learning. Informal enquiries may be addressed to Prof. Andrea Vedaldi (email:andrea.vedaldi@eng.ox.ac.uk) For more information about working at