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, Evolution, and Disease. We are looking for a PhD with a strong quantitative background and hands-on experience in either machine learning force field estimation or modern generative models, who is eager about
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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for improved cancer understanding, diagnostics, and
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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for precision medicine and clinical decision support? Would
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on applying AI and machine learning to molecular design challenges. This position is one of several industrial PhD roles funded by the DDLS program, which supports training in four strategic areas: cell and
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of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance
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particularly valuable. Documented experience with machine learning and biostatistics is also highly meritorious.You can find information about education at postgraduate level, eligibility requirements and
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in computer science, engineering, data sciences, applied mathematics, machine learning, or another related field; or Have completed at least 240 credits in higher education, with at least 60 credits at
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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hampers our ability to establish causal relations between molecular alterations and disease phenotypes. In this PhD you will address this by developing a deep learning model of cancer. The PhD position