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Science at Queen Mary University of London, working with Professor Rachel Humphris and Dr Dimitrios Kollias. The successful applicant will undertake computational research, including algorithmic auditing
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capable of supporting and collaborating with humans in complex, real-world settings. You will be responsible for researching and developing novel algorithms and techniques to achieve the project’s
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Computer Science at Queen Mary University of London, working with Professor Rachel Humphris and Dr Dimitrios Kollias. The successful applicant will undertake computational research, including algorithmic
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will develop and apply computational methods for the analysis of cell-free DNA (cfDNA) sequencing data, supporting a growing research program at the intersection of epigenomics and translational medicine
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Prof. Neil Walton (Durham University, UK). The general aim of this project is to develop throughput-optimal entanglement distribution algorithms (both centralized and decentralized algorithms
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are twofold. The first goal is to accelerate the solution of the large mixed-integer optimisation problems required to balance energy. The second goal is to develop methods that handle the increasing
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to trace how welfare algorithms operate in practice. They will also contribute to comparative analysis across case study countries, support interdisciplinary collaboration, engage with external stakeholders
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second goal is to develop methods that handle the increasing uncertainty associated with high renewable penetration in a more systematic and effective way. Specific responsibilities may include: Developing
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and data processing skills: experience of programming in one or more languages (e.g. R, C/C++, Python, Matlab). Practical experience of algorithm development and implementation of machine learning
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, including but not limited to embedded/hardware security, security of AI systems, (post-quantum) cryptography, quantum algorithms, confidential computing/trusted execution, or microarchitectural security. Key