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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, based at the Department of Computer
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identification and machine learning. The key challenge is striking a balance between, on the one hand, modelling the physical, dynamic and nonlinear behavior of the components with sufficient physical accuracy
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and improve computational methods for the pre-processing of MS data, exploring new algorithmic approaches for signal detection, deconvolution, and feature extraction. Machine Learning for Chemical
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at the local level, within households, communities, and local politics. The project combines large-scale surveys, survey experiments, administrative and archival data, GIS, and qualitative field research in
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allocation mechanisms, with a particular focus on the efficiency and fairness of Eurotransplant’s liver allocation system. Information We are looking for a strong, motivated PhD-student with an analytical
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software engineering, computer science, data science, bioengineering, bioinformatics, engineering, physics or related Experience in either machine learning or computational biology. Interest in both
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on causal and mechanistic studies of microbiome-mediated pathogenesis. This is achieved by bridging microbiology and big data analytics in a structured doctoral training environment. The need of microbiome
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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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software engineering, computer science, data science, bioengineering, bioinformatics, engineering, physics or related Experience in either machine learning or computational biology. Interest in both
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to incorporate additional field data. This PhD project offers a great opportunity to work with large-scale biodiversity and climate datasets, develop strong analytical skills, and collaborate with international