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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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such as Neuro-AI, AI for Medicine, AI for Biodiversity, Systems Biology, and Algorithms. Develop strong links with partners across the Faculty of Science and Engineering — including Advanced Computing
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: questionnaires on healthcare and patient outcomes, qualitative data on patient experiences, improved diagnostics using innovative laboratory methods, development of pathophysiology-based treatment plans
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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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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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) Assessing the performance and fault tolerance of neuromorphic hardware; (b) Designing and developing one or more machine learning (ML) and artificial intelligence (AI) algorithms to support and enhance
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using innovative laboratory methods, development of pathophysiology-based treatment plans, identification of biomarkers and haemostatic modifiers with multi-omics approaches, an AI-driven bleeding
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. You will take the lead on applied physics, mechanics, manufacturing processes, and algorithm/coding development within the bioprinting domain. This position is part of a larger, EU-funded Horizon Europe
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in using AI technology in citizen-state interactions. How can we design fair algorithms, and how can we govern AI-related risks? The position is funded for a period of 18 months, preferably starting
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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