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The Rantalainen group is focused on application of machine learning and AI for development and validation of predictive models for cancer precision medicine, with a particular focus computational pathology. Our
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-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality
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sequencing, and with computer scientists at KTH in Stockholm, focused on developing scalable probabilistic machine learning techniques for online phylogenomic analysis and placement of DNA barcodes. You will
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managing large amounts of data by designing structured databases (PostgreSQL, MySQL). Machine learning methods such deep learning for analysis of proteomics data and classification of cancer profiles. Since
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the state of soils and waters. The department is responsible for several important research infrastructures in the form of soil chemistry and soil physics laboratories, a computer tomography, a lysimeter
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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, implementation of methods in computer codes, use of state-of-the-art high-performance computers in Sweden and in Europe, application of machine-learning and AI techniques, and collaborations with experimental
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academia and industry. Requirements The following qualifications are required: Solid knowledge in mathematics and statistics, in areas such as linear algebra, probability theory, machine learning, high
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systems, and machine learning. While the initial focus of the position is on this project, we offer significant opportunity for the applicant to develop their own independent research trajectory in
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of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. More information about the total announced post-doctoral positions within in