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Field
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Overview: This exciting PhD opportunity is at the intersection of aerospace engineering and cutting-edge technology. It focuses on developing an innovative ground-based robotic inspection system
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We are searching for a doctoral candidate eager to take part in crossdisciplinarity work within battery technology for a sustainable future. This work will compose both theoretical and experimental
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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cross-layer defenses that ensure secure and efficient AI model development at scale. Information about the division The department of Computer Science and Engineering is strongly international, with
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Biomedical Engineering conducts leading research in image analysis, computer vision, and machine learning, with a growing emphasis on generative AI and AI for scientific discovery. Our mission is to develop
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are deeply committed to environmental stewardship and eager to apply their specialized skills in AI, data analysis, software development, and electrical or energy engineering to make a significant and tangible
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plus RF and microwave engineering. Hands-on experience with software defined radios (SDRs) like USRPs is considered a plus Statistical signal processing Resource allocation and optimization
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engineering and/or timber engineering. Experience in scientific timber-related laboratory work Knowledge of Finite Element software programs (e.g. Abaqus and OpenSees or similar) Programming skills (e.g. Matlab
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analysis and analytical data analysis workflows, together with other team members Implementing AI-based microscopy image analysis software as python packages Developing algorithms to deploy machine learning
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Qualification: The candidate should possess a MSc. Degree or equivalent in Engineering, Computer Science, or related fields. Experience: The ideal candidate should have some knowledge and experience