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innovation with clinical relevance and real-world impact. Postdoctoral Researcher Explainable AI and Foundation Models for CT Imaging Our goal: To develop and validate novel AI methods that enhance
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of interaction and urban design, where your research can shape the vision of open and accessible cities! Join Us! This postdoctoral position integrates data-driven and human-centered research methods first to
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in populations under selection. However, currently, no unbiased method exists to accurately estimate genetic variance in populations under selection. The GEN project aims to develop and validate a
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how to engineer their spectral response for multiparameter sensing, guided by fundamental bounds on estimation precision, and implement advanced computational design methods to realize optimal
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Models to push the frontier where computer vision, physics simulation, and embodied AI converge. Join Us! This position is part of a collaborative research programme between the University of Amsterdam
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. The focus will be on enriching statistical methods through advanced machine learning techniques, for instance, by learning latent representations of the data. In addition to utilizing such techniques
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throughout the early phases of missions, including participation in CDF and phase A/B1. The Team also provides expertise to other projects and studies, including research and development of tools and methods
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for resilience, and engaging with key stakeholders across the European space and security ecosystem. Main research topics: EO-driven threat detection and situational awareness: develop innovative methods
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, extending them to perform pluralistic alignment. To enhance model interpretability, we will also develop methods to better understand the mechanisms of cross-lingual transfer in LLMs and their cultural
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of Psychology, working as part of a unique interdisciplinary team spanning Psychology, Informatics, and Digital History. By applying computational social science or computational humanities methods to large-scale