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-or-leave decisions, but how we make them is not well understood. The goal of this project is to find out if there is common cross-species decision algorithm for leaving and what that algorithm is. You will
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subject from a recognised institution. A background in at least one of the following: Dynamical systems Photonics/Electromagnetics theory, design and simulations Machine learning mathematics and algorithms
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/Electromagnetics theory, design and simulations Machinelearning mathematics and algorithms Numerical methods Programming skills (Python, MATLAB, or similar) Strong analytical and problem-solving skills. Good written
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of algorithmic systems. The research will investigate how clinicians interact with automated and machine learning–based decision-support systems, with a particular focus on cognitive workload, trust, situational
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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on developing the simulation models, data models and algorithms required to enable connected cross-disciplinary design and optimisation, laying the foundations for more integrated and intelligent engineering
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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. Expect close collaboration with industrial experts and the opportunity to see your algorithms influence aerospace and other high-value manufacturing sectors. Funding and eligibility 3-year, full-time PhD
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individuals whose work addresses substantive economic questions—such as causal inference in high-dimensional settings, algorithmic behavioral economics, forecasting economic indicators, or modeling complex
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algorithms. This is an exciting multidisciplinary PhD project that promises to make cutting-edge advances in all research areas involved. Aim This project combines practical hands-on optics experimentation