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look forward to receiving your application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems
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, computer science, electrical engineering, applied mathematics, machine learning, or in a similar field, or have completed at least 240 credits in higher education, with at least 60 credits at Master’s level
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flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
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combines: Fluid dynamics and heat transfer (theory and experiments), Computational modeling, and Machine learning / computer vision for data analysis and pattern recognition. The goal is to improve
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multiphase flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
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quantified, and machine learning will be used. Duties As a PhD student, you will work toward a doctoral degree as the final goal, according to the goals specified in the Higher Education Ordinance. In parallel
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that you have a PhD in natural sciences/technology/medicine/mathematics/physics or equivalent, with a focus on machine learning, Excellent oral and written English skills, Publications in machine learning
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experience with advanced signal processing concepts as well as digital filters is advantageous. Your workplace You will be working at the Division of Electronics and Computer Engineering (ELDA), which conducts
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and 3D electromagnetic simulations is considered a significant advantage. Your workplace You will be working at the Division of Electronics and Computer Engineering (ELDA), which conducts teaching and
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paraganglioma driven by cell plasticity using spatial transcriptomics and machine learning.” High-risk neuroblastoma (NB) and malignant paraganglioma (PPGL) are neural crest–derived tumors with pronounced