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these datasets to detect chromosomal abnormalities and study their breakpoints. Using statistical methods and machine learning, we will explore how these structural variants arise and which recurring structures
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. The successful candidate will work on cutting-edge projects involving artificial intelligence (AI) and computational pathology, with a particular focus on developing and applying machine learning algorithms
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psychiatry. The projects will involve advanced epidemiology, pharmacoepidemiology, and machine learning methods. You will be part of a well-funded and successful research group, collaborating with
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such as epidemiology, biostatistics, computer science, statistics, etc. We will also consider those with PhDs in other areas but who have advanced/relevant data science skills (e.g., machine learning
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use the data to train deep learning models of cancer. This allows us to identify systems-level mechanisms that can be used to uncover new biomarkers, drug targets, and paths to drug resistance. We
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work on bioinformatics, machine learning of transcriptome data and differential analyses of microbiome data, all within a European project funded by the Innovative Medicines Initiative Joint Undertaking
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such as epidemiology, biostatistics, computer science, statistics, etc. We will also consider those with PhDs in other areas but who have advanced/relevant data science skills (e.g., machine learning
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and behavioral measures, and on social cognitive decisions about the attention of others. In one of the projects, advanced behavioral methods, machine learning and eye tracking (simultaneously in two