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aims to digitalize the sense of smell, laying the foundation for understanding how olfaction works in humans and for building AI models that simulate olfactory experiences. The research will focus
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MultigrainGIS: Grain-adaptive geographic data processing for ecological modeling (https://drive.google.com/file/d/1s0wSsXd8OQN-xm1KOFVGHTNVOyLv8-OZ/view?usp=sharing ), funded by the Swedish Research Council
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employment decision is made. Doctoral degree in remote sensing, geoinformatics, computer science, or a closely related field. You have experience developing and applying deep learning models for Earth
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Technology We invite applications for a fully funded WASP-PhD position to join the new research group of Martin Trapp to work on the reliability and trustworthiness of machine learning models. You will work
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PhD with a background in science and technology studies (STS), human-robot interaction (HRI), human-computer interaction (HCI) or social sciences. The project aims to develop a Nordic Model for
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reconstruction. We will use physics modeling, machine learning and experiments to develop new and improved methods for using data from energy-sensitive x-ray detectors to improve the diagnostic quality of x-ray
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techniques to model fluid turbulence, fusion plasmas (with a particular focus on inertial confinement fusion target design), and quantum circuit simulators. The work will range from algorithmic and theoretical
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accordingly. To connect local material properties to macroscale asphalt pavement performance, you will employ multi-scale numerical modelling based on the Finite Element method. This project is a collaboration
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experimental platform and combine it with continuum modeling of complex materials and machine-learning-based analysis methods to understand and predict biofilm structure and growth. Supervision: Shervin Bagheri
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system control, particularly in vehicles or buildings. Experience with field measurements, data collection, and energy use analysis. Knowledge of simulation and modeling of energy systems, preferably using