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group has expertise in radiology, biostatistics and machine learning. We have a strong collaboration with research groups at KTH, at KI, and internationally within two EU projects and a new collaboration
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collectively offer expertise in computational biology, genetics, epidemiology, and machine learning. The research will be closely linked to the WISDOM project, an EU-funded initiative coordinated by the main
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of four years of full-time doctoral education is required. One Ph.D. position is available in cancer precision medicine using advanced machine learning methods and AI methods on large-scale data
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of the doctoral student The PhD project will aim at integrating single cell clonal, spatial and dissociated cell transcriptomics data for 3D neurodevelopmental reconstruction using a machine learning approach and
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information from sequence alone, independent from optical microscopy. This adjacency or neighbor-neighbor information can be used generate images in a computer. Today one person can routinely read millions
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medicine strategies for improving diagnostics and treatment of prostate cancer. The research spans world-leading data sources, innovative clinical trials, cutting edge genomics, machine learning and
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trials, cutting edge genomics, machine learning and artificial intelligence. The doctoral student project and the duties of the doctoral student The work aims at improving prostate cancer care by
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-house sequencing machines, processing of sequencing data, including running the computational tools in the lab for systematic de novo capturing of splicing patterns and mapping to cell types. We are also
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this deadly disease. Specifically, the student will develop and apply sensitive methods for MS-based analysis of clinical lung cancer samples. Further, the student will apply machine learning methods
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in biological aging and proteomics. Familiar with ways of measuring aging. A keen interest in data-driven research and interdisciplinary science, including bioinformatics, systems biology, machine