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if other criteria are met. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is desirable but learning can be completed during the PhD. Excellent
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loading rate effects on constitutive properties of modern engineering materials. Machine learning based meta models for complex engineering system simulation. Thermodynamics & Fluid Mechanics Development
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relate to the interests of one of the School’s research groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security
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microscopy data will be analysed using a range of machine learning techniques and artificial intelligence. This project is based on a long-term collaboration between the Biophotonics Group (School of Physics
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, advanced quantitative methods, data skills and machine learning methods for effectively handling micro-level panel data, providing valuable skills for future careers. A Masters degree is not a prerequisite
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Automation, Machine Learning Overview: This 36-month funded PhD studentship will contribute to cutting-edge advancements in reaction optimisation through the integration of high data-density reaction
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PhD Studentship: A continual learning approach for the development of robust robotic control systems
of these systems, being the foundation of computer vision, monitoring, and control solutions. Despite the promising results that AI (and especially Deep Learning) has shown in these application areas
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View All Vacancies Engineering Location: UK Other Closing Date: Sunday 15 September 2024 Reference: ENG1725 Applications are invited for a PhD project within the Faculty of Engineering, in
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perspective. The incorporation of data-driven techniques, such as machine learning approaches, will enrich the scope of the project. Students engaged in this project will potentially have the chance to