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following its curriculum. The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous
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to have good knowledge of computer science, mathematics, algorithms, and programming. Knowledge and experience in artificial intelligence and machine learning is expected, but not required. Knowledge and
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addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent
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, algorithms, and programming. Knowledge and experience in artificial intelligence and machine learning is expected, but not required. Knowledge and experience in deep learning and generative AI is considered
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area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports
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Sweden’s national infrastructure for visualization of scientific data. Currently, InfraVis employs over 50 experts across nine universities. CIPA is Lund University’s local infrastructure for image
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transcriptomics data, so familiarity with RNA-seq analysis, data visualization, and computational workflowsis required. The candidate should have a strong motivation to apply computational approaches to biological
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bioinformatics pipelines for the metabolomics data analysis and visualization of metabolomics data, support the integration of software tools for data (pre-)processing, biomarker discovery, and predictive
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and visualization of metabolomics data, support the integration of software tools for data (pre-)processing, biomarker discovery, and predictive modelling. Furthermore, serve as the metabolomics subject
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on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems