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position on GW data analysis using machine learning (ML) with expected starting date February 2026. The position focuses on using neural posterior estimation for tackling issues related to the analysis
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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renewable energy generation.KU Leuven leads Modelling and Optimization, which focuses on: Developing hybrid models combining first-principle and machine learning approaches. Creating predictive frameworks
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work actively on the preparation and defence of a PhD thesis in the crossroads between the fields of robotics, signal processing and machine learning The candidate will explore how graph-based
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Educational Master – and conducts research across a wide variety of domains in each of these fields. The faculty’s vision can be summarized as: “With trust, in connection, through continuous learning.” The FPPW
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computer scientist who can lead a research group where the development of new machine learning techniques serves as an important basis for tackling challenging biotechnological issues. Your achievements in
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), user interface design, or data visualization techniques. Familiarity with frameworks for explainable machine learning (e.g., SHAP, LIME, Captum, Alibi). Experience in designing context-aware, adaptive
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experience in common deep learning frameworks (e.g., PyTorch and TensorFlow) would be a benefit; The qualities to carry out independent research, demonstrated e.g., by the grades obtained in your (under
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KU Leuven has a vacancy at Campus De Nayer for a full-time professor in Intelligent Software, advanced software that combines machine learning and knowledge-based inference. We are looking
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generation of spectroscopic sensors, integrating spectroscopic analysis, machine learning-based data processing, miniaturized sensor development, and industrial validation. As a Technology Expert, you will