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in our mission to develop clinically useful algorithms, drive high-impact publications, and pave the way for personalised breast cancer treatments. Analyse data from cutting-edge technologies
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in our mission to develop clinically useful algorithms, drive high-impact publications, and pave the way for personalised breast cancer treatments. Analyse data from cutting-edge technologies
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enable the development and operation of new algorithms and software to solve leading-edge research problems. You will find this work exciting if you: Want to help build and maintain some of the largest
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. Philipp Petersen, M.Sc.. The research areas developed by the team are in particular related to theoretical analysis of classical problems in numerical analysis in the framework of modern algorithms
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maintenance, production efficiency, and quality control. While the benefits of ML are significant, its adoption also introduces risks such as data privacy concerns, algorithmic bias, model transparency issues
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foundation models, multi-modal learning algorithms, generative models, and large language models [1], have made seen remarkable advancements in the field of healthcare. It can lead to more accurate diagnosis
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in simulated environments and with real data on real UAVs. Defining and calculating measures for levels of trust in the developed algorithms is essential. These uncertainty-aware algorithms can self
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Deadline: 30 June 2025 Details This project aims to develop new algorithms for reinforcement learning from human feedback, to effectively solve complex reinforcement learning tasks without a predefined
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information from ‘deep tissue phenotyping’ datasets. The successful applicant will have significant experience working with machine learning algorithms. They will have strong Python programming skills and
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, programming languages, data structures and algorithms, operating systems, network security, visualization, and human-computer interaction, as well as participate in the full range of faculty responsibilities