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, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision, digital pathology, whole-slide image analysis, self-supervised learning, foundation models, multiple
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at least one deep-learning framework (PyTorch preferred).•A solid grounding in machine learning. Experience with representation learning, generative models, foundation models or multimodal integration is a
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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19 Aug 2026 Job Information Organisation/Company KU LEUVEN Research Field Engineering » Electrical engineering Engineering » Electronic engineering Engineering » Computer engineering Computer
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. The research will involve training machine-learning models on large structure and sequence datasets and integrating membrane-specific biophysical constraints to enable the design of membrane proteins and
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experience in Python and, more specifically, in common deep learning frameworks such as PyTorch and jax, for model training and inference have experience with embedded platforms such as FPGAs or RISC-V
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-order modelling, surrogate models, and machine-learning methods such as neural networks. Control design for flexible reactor operation. Develop advanced control strategies that enable safe and efficient
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for using AI to develop social engineering attempts. This project combines human subject research of learning and decision making, Human-Computer Interaction, and the advancement in AI methods
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strong interest in machine learning/artificial intelligence. You have experience with deep learning. You have experience with reinforcement learning (preferred). You have experience with explainable and/or
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and cooperation. You have a strong interest in machine learning/artificial intelligence. You have experience with deep learning. You have experience with reinforcement learning (preferred). You have