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Deep Learning (CIDL), part of the Leiden Institute of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from
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of the following: Experience with Explainable AI. Experience with Deep Learning. An interdisciplinary background / interdisciplinary training. Have followed courses in Psychology or Philosophy
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skills: Good knowledge of ML/AI based techniques to develop fast surrogates (deep neural networks) and capability to develop own efficient model learning schemes (deep learning techniques, representation
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-design. Experience with hardware acceleration (FPGAs, GPUs, SoCs) and low-power design. Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow) is a plus. Ability to work in an
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, or related background. Strong background in machine learning, computer vision, and deep learning. Knowledge of transformer architectures and foundation models. Experience with few-shot learning, self
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interested in using AI to unravel the mysteries of the brain? Do you want to perform cutting-edge NeuroAI research and leverage deep learning to understand human vision? Then check out the vacancy below and
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, interdisciplinary project. At the end of the project, you will have: a deep understanding of the hydrodynamic processes that control the dispersion of buoyant macroplastic items in the coastal zone; expertise in
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. Upwelling events bring nutrient rich deep-water to the surface, promoting phytoplankton production through communities dominated by known producers of omega-3. As such, these areas could represent hot-spots
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the composition and functioning of microbial communities in environments ranging from the deep sea to large lake systems. Within this department a subgroup of organic geochemists is developing novel (analytical
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designers of their workplace rather than passive recipients of noise measurements. The research will follow an iterative research and development process characterized by deep, on-site engagement with NPICU