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or hydrogen, or geothermal energy production) have fundamentally different characteristics compared to natural earthquakes. Understanding the essential non-stationary character of the processes that caused
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, LLMs can translate natural language querries into a compatible format for popular databases (e.g., MySQL, Neo4j) thus expanding existing knowledge bases. By enabling more efficient search and discovery
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of energy-efficient solutions (i.e., minimizing both communication, processing and memory resource), these mobile systems will be autonomous and will rely heavily on on-board inference. In this project
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. Experience in machine learning, natural language processing, and deep learning is also a plus. A Master's degree in computer science, artificial intelligence, or a related field Strong programming skills in
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My group is interested in biological signal processing, especially in the context of chemical stimuli in gene regulation and development on the one, and macroscopic stimuli (light, touch
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for the decision-making process. By addressing the black-box nature of machine learning models, you will bring clarity and predictability to your models. Trust will be earned as you evaluate the robustness of your
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research, including the first chronic animal trials, to produce a soft artificial heart. Our goal is to mimic the natural contraction of the heart as much as possible, by generating a pulsatile flow, and
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English and good communication skills. Dutch language skills are required, given the nature of the empirical work required. You have excellent study results, and academic writing skills are regarded as
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Would you like to join an interdisciplinary team that combines systems and control theory and geomechanics to understand what drives earthquake processes? The research programme DeepNL aims
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centralization of pediatric cardiac surgery. The recent debates on delivering these types of care often make it to newspaper headlines. In both cases, changes in care provision are expected to take effect in