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Field
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applicants who demonstrate substantial hands-on experience implementing, training and evaluating deep-learning models will be considered. General interest in AI or experience limited to running tutorials
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requirements for admission to the PhD programme Experience implementing and modifying deep learning architectures. Working knowledge of Python and a modern deep learning framework. Strong programming skills in
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intelligence, computer science, remote sensing, geomatics, data science, or a forest/environmental science discipline with a strong quantitative or AI component Strong knowledge of machine learning and deep
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language processing that address concrete problems and are both theoretically rigorous and interpretable. The PhD is funded by the ERC CoG PANDORA (Deep Multimodal Learning for Mining and Generation of Arguments
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and apply machine learning and deep learning models to analyse complex, multi-dimensional datasets, including spatial transcriptomic, proteomic, and single-cell sequencing data. The candidate will
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, computational biology, statistics or a closely related field. You have strong programming skills, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision
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degree in Computer Science, Artificial Intelligence, Robotics, Electrical Engineering, or a closely related field. A strong academic record and solid background in machine learning and deep learning
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planning and decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch
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interpreted using deep learning to estimate tool-to-retina distance and generate accurate three-dimensional navigation commands without relying on conventional 3D reconstruction. Research Objectives
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with deep generative models (VAEs, GANs, diffusion models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as