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12th December 2025 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in Algorithmic Fairness in Recommender Systems Apply for this job See
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, enabling algorithm–circuit co-optimization across the computing pipeline with respect to key metrics such as power consumption, computational delay, and area efficiency. Beyond circuit prototyping
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specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in the computational biology and
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by: Developing specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in
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(rhizotron facility) and field trials. In addition to field applications, novel inversion algorithms for ground-penetrating radar (GPR) and electromagnetic (EM) will be developed. These algorithms will enable
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unit and then pre-processed data used as the input of the deep learning algorithm. The research will employ the SafeML tool (a novel open-source safety monitoring tool) to measure the statistical
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two distinct images from a single PET acquisition. Within this project, we will jointly develop, adapt and implement advanced image reconstruction algorithms in our in-house reconstruction software
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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as well as small-scale EMI measurements with root and shoot observations in controlled experiments (rhizotron facility) and field trials. In addition to field applications, novel inversion algorithms
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, the project will develop algorithms for ecological sensing, adaptive motion planning, and energy optimisation under real-world constraints. Scaled experiments and high-fidelity simulations will validate system