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of Amsterdam. Interested in developing fundamental machine learning techniques for tabular data to democratize insights from high-value structured data? Then this fully-funded 4-year PhD position starting Fall
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(due to the low radiation dose). One possible way to address this is to incorporate information gained from previous scans (e.g., MRI) of the same patient. As a PhD student on this project, you will
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, which is crucial for rutting, using machine learning. Second, we will develop new systems to integrate data from radar and lidar sensors mounted on drones and forestry machines to improve future real-time
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and may commence preferably in the fall of 2025. Your tasks As a PhD student at DTU, your work will include: Learn to perform rigorous and relevant research Collaborate with key academic and/or
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. Please submit these documents as a single pdf. Please include “PhD Application (Interpretable Machine Learning)” followed by your name in the subject line. The application CV should, at minimum, include
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candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of molecular data in cancer genomics. The position is connected
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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical
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foundation for theory-guided catalyst design e. g. by machine learning approaches. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality within
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approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat