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Field
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intelligence (AI), and high-performance computing (HPC), as well as quantum-inspired algorithms and quantum machine learning (QML). Responsibilities: Lead and contribute to applied quantum computing research
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learning, physical AI, and spatial AI. The RA will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the Physical Vision
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industry value in the short to medium term. This includes applications combining quantum computing, artificial intelligence (AI), and high-performance computing (HPC), as well as quantum-inspired algorithms
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sensor data, including LIDAR and camera inputs, for robotics and automation applications. Conduct outdoor vehicle trials for testing and validation of perception, navigation algorithms, and self-driving
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computational biologist to collaborate with a multidisciplinary team to develop innovative computational algorithms and approaches to address crucial questions in cancer biology. The role will involve
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programming, algorithms, and systems. A willingness to grow into unfamiliar courses matters more to us than existing coverage of every topic. As a small department, every faculty member’s flexibility keeps all
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novel quantum systems and algorithms, exploring qubit design, quantum error correction, and scalable computation architectures. The candidate is also expected to contribute to quantum simulation
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developing quantitative evaluation methodologies or performance metrics. Strong programming skills in Python and modern AI frameworks (e.g., PyTorch, Hugging Face). Experience with optimization algorithms
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Interaction and Human-Centred Computing Computer Vision and Multimedia Natural Language Processing Robotics and Autonomous Systems Algorithms, Optimisation and Theoretical Computer Science Responsible
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but not limited to the following areas of Computer Science: Object-oriented programming, Data Structures and Algorithms, Software Development on Windows/Unix platforms, Web development, Artificial