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Field
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advanced AI methods to extract meaningful knowledge from large-scale, heterogeneous, and high-dimensional biomedical and population data, often referred to as Big Data in the health and life sciences
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. Computational methods and artificial intelligence applied to large-scale molecular data are transforming the study of biological systems at all levels, from molecular structures and cellular processes to human
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facility. Good understanding of how pre-analytical and laboratory methods can affect data quality. Quality control and analysis of large-scale proteomics data. Experience working in an accredited environment
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Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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statistical programming and statistical analysis experience in data management, and working with register data or large micro-level longitudinal databases experience in working with health inequalities and/or
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learning, using large-scale Neuropixels recordings combined with computational modelling. The project is embedded in a national network of data-driven life science research spanning eleven Swedish
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participate in clinical work and teaching; contribute to the strategic development of the department, faculty and SLU; communicate research findings and other relevant information to society at large; perform
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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focus on building scalable solutions for large-scale data processing and model training. Experience in working with multimodal or vision models. Experience in working with optimization approaches. Good
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values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your