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Field
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, once the codes have been tested and validated, the work will involve performing simulations of materials for energy storage (batteries, supercapacitors), in collaboration with our partners in Japan (Prof
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have an exciting PhD position for you. Extreme precipitation is likely to increase with climate change in large parts of the world. In the tropics, extreme precipitation is often associated with
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for greater precision. Machine learning (ML) algorithms will analyse these datasets to deliver a scalable, cost-effective system, validated through field trials and enhanced by contributions from four
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will work closely with the PI (Prof. Dawar) in a team of other researchers on the project and actively participate in the Logic and Algorithms research group. Candidates will have completed a Masters
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with data science, and data management (including IoT, Edge, and HPC). This is a fully funded position for 24 months within the HEXAPIC project, conducted in collaboration with Prof. Leon Kos' team
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), Machine Learning on Quantum Computers, Security of Quantum Circuits, Design Automation and Tools for Quantum Circuits, Robust and Efficient Mapping of Quantum Algorithms on Quantum Machines, Quantum Noise
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) or neural network-based methods. The level of the targeted problems will require further mathematical and algorithmic developments over the current state of data-driven SSM reduction. The PhD position will
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inviting applications for a PhD Student (f/m/x) for the project Theory and Algorithms for Structure Determination from Single Molecule X-Ray Scattering Images Project description Single molecule X-ray
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Digital twin railway network School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof D Fletcher, Prof R Harrison Application Deadline: Applications accepted all
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This PhD position offers a unique opportunity to advance safe and transparent control for autonomous, over-actuated electric vehicles. You will work at the intersection of model predictive control