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Field
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for latent variables and their connections to modern machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates
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modeling, computer simulation, non-linear model analysis, interactive learning environments and decision-laboratory experiments. About the project/work tasks: Description of the INTEGRATOR project
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; machine learning or deep learning; pharmacogenomics; computational biology; drug discovery; network medicine; NLP/large language models; or precision medicine 2. Strong programming skills in Python, R
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architectures for foundation models The work will combine methodological development with large-scale experiments, aiming for contributions at leading machine learning and computer vision venues such as NeurIPS
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machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates will have the opportunity to collaborate closely
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BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and
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and structure of healthy anatomy and detect any deviation from the healthy distribution. But in the absence of labels, how should we direct the model to learn relevant features, and how can we determine
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project
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. The successful candidate will combine extensive experimental testing with insulation lifetime modelling to study PD inception, degradation and endurance, and to develop approaches for predicting insulation
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deep-learning and 3D computer-vision models that detect features while representing a distribution of plausible interpretations. Encode geological relationships in a knowledge graph that stores