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Field
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is an emerging research field that uses machine learning, data analysis and computational modelling to guide the discovery, characterization and optimization of new materials. By accelerating
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mathematics, or a related field Practical experience with AI, machine learning, data analytics, or related computational methods Ability to apply technical knowledge to real-world problems Experience
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): Experience in AI algorithms, and machine learning Experience in Spatial proteomics Experience in splicing analysis The applicant must be able to integrate well into the international and multidisciplinary
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materials, XRD with Rietveld analysis, SEM, TG, DSC, micro-CT, particle size analysis, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is
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) will work at the interface of structural bioinformatics, machine learning, and membrane biology, in close collaboration with experimental groups in membrane biology and structural biology. The Elofsson
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record of publications at leading venues in social science, machine learning, natural language processing, statistics, or computational social science is highly meritorious. You are a self-driven and
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professional approach, analyze and work with complex issues and demonstrate experience with programming languages such as Python or C++. We seek candidates with a background in machine learning, robotics and
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, writing, speaking). • Show ability to work independently as well as in a team. • Good knowledge in AI, machine learning, data science and mathematics. • Good knowledge in one or more of the following
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computational studies and, where appropriate, modern analysis methods such as machine learning. The student will contribute to feasibility and sensitivity studies for proposed future experiments and work
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machine learning and experience with computer vision and/or remote sensing is highly desirable and especially meritorious. After the qualification requirements, great emphasis will be placed on personal