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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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knowledge gap in cancer immunobiology and supports the development of more accurate disease models. Duties This is a unique opportunity to shape the research direction itself: you will be central to building
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https://www.kth.se/is/dcs/ . Supervision: Prof. Matthieu Barreau, Alexandre Proutiere, Anna Herland, and Avlant Nilsson is proposed to supervise the doctoral student. Decisions are made on admission
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, proteomics, long-read sequencing). Familiarity with machine learning approaches, particularly artificial neural networks, and their application to biological data. Experience with workflow management systems