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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Chemistry, Department of Chemistry – BMC The Department of Chemistry – BMC conducts research and education in analytical
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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Chemistry, Department of Chemistry – BMC The Department of Chemistry – BMC conducts research and education in analytical
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Are you interested in developing computational tools and learning strategies for understanding health and disease at the microscopic scale? Would you like to be part of a research team with skilled
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. We care about creating a positive, respectful, and stimulating environment, valuing communication and collaboration and a workplace that promotes learning and development for all. We are committed
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are looking for a highly motivated, independent, and analytical person, with: A degree or the equivalent in scientific data analysis, data science and machine learning, computer science, bioinformatics
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data analysis, programming, and biology. You will be part of a collaborative research team with deep experimental and analytical expertise, with access to advanced tumor models and state-of-the-art
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academic background with thorough computational and analytical understanding; Proficiency in programming in Python and deep learning frameworks such as PyTorch and TensorFlow; Excellent communication skills
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) biological knowledge about GRNs from bioinformatics and system biology, (b) graph theory and topological data analysis for network modeling from mathematics, and (c) robust machine learning (ML) and GenAI from
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interdisciplinary project. The project concerns algorithm design, implementations of algorithms, and simulated and biological data analysis. The student is expected to learn a bit of relevant molecular biology to
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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