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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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aim to develop a predictive model identifying advanced HF patients at high mortality risk within a year. Additionally, we plan an intuitive interface, utilizing large language models to communicate
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of Organic Energy Materials and Green Polymer Chemistry (GPC ). At OED we explore the conversions of biomaterials from forest, air components, and water at electrochemical interfaces in flow devices aiming
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activities, which also include responsibility for the master's programme in Naval Architecture and Ocean Engineering and contributions to the education of seafarers. Your profile To qualify for this position
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from the European Research Council and a DDLS Fellowship from the SciLifeLab and Wallenberg Swedish program for data-driven life science. The successful candidate will be working within the development
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nitride (hBN)-based thermal interface material in this project. The hBN material offers high thermal transfer performance while providing electrical insulation for AI booted electronics and battery cooling
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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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across Sweden and beyond. At NGI, you will be part of a dynamic environment with access to a broad range of instruments, high throughput automation, and strong computational expertise (https
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to develop solutions with real world relevance and impact. This project will be carried out in close collaboration with researchers from the Division of Material and Computational Mechanics at IMS and the
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to work at the interface of nanotechnology and stem cell biology in a creative and collaborative research environment. The position is full-time for two years with the possibility of extension. Your mission