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Description We are looking for a PhD-candidate interested in topics that lie on the border of optimization by the use of heuristic algorithms and (Explainable) Artificial Intelligence ((X)AI). Specifically, in
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require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will: Develop efficient numerical methods and strategies to solve the electromagnetic
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cryptography guarantees better performance and faster speed for encrypting data. Without doubt, AES (Advanced Encryption Standard) and Keccak/SHA-3 (Secure Hash Algorithm 3) are the two most used and famous
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particle physics, perform data analysis and develop object reconstruction algorithms in the ATLAS experiment. You will become a member of the ATLAS collaboration and will be based in Nijmegen. Furthermore
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase
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Hunger Lab at Tilburg University, and four industry partners. In this project, you will develop and advance optimization models and algorithms to support decision-making in food supply chains, with
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focus will be on developing compact, efficient, and real-time LLM algorithms/hardware on the edge and developing demos for specific applications such as speech disorder therapy. Your responsibilities will
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new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms. What you will do You will carry out research and development in the areas
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-tuning algorithms. What you will do You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to
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on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order models, designing controllers that exploit