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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches
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to work on meaningful projects with direct clinical relevance. About the role In this role, you will develop and implement computer vision and deep learning algorithms to analyse CT and MRI data from
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches
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fundamental algorithms for producing policies for rich goal structures in MDPs (e.g. risk, temporal logic, or probabilistic objectives), and modelling robot decision problems using MDPs (e.g. human-robot
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We are seeking to recruit a motivated postdoctoral researcher in Verification and Game Theory. You will enjoy developing algorithms, lower bounds, and possibly proof-of-concept implementations
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learning methods to improve the understanding, treatment and prevention of human disease. The successful candidate will develop novel statistical and machine learning algorithms to address key challenges in
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research in neuro-symbolic AI, with a focus on using generative AI and prompt engineering as a method to engineer knowledge graphs one can trust. This includes the design of algorithms and architectures, but
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machine learning methods to improve the understanding, treatment and prevention of human disease. The successful candidate will develop novel statistical and machine learning algorithms to address key
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research in neuro-symbolic AI, with a focus on using generative AI and prompt engineering as a method to engineer knowledge graphs one can trust. This includes the design of algorithms and architectures, but
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encouraged to adopt a creative approach to problem-solving, exploring various deep learning techniques. Verification of these models and algorithms will be conducted using benchmark datasets and real-world