43 parallel-computing-numerical-methods-"Multiple" positions at Linköping University in Sweden
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identification, optimization, or numerical methods is valuable, as is knowledge of data analysis and machine learning for complex, high-dimensional systems. Programming experience in MATLAB or Python, and an
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application! We are now looking for a PhD student in Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Your task will be to analyse and adapt vision
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numerical analysis, computational fluid dynamics, and uncertainty quantification with diverse applications. Our group maintains active collaborations with other divisions at Linköping University and broader
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NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by
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research at LiU focuses on securing the most critical functions of digital society. Through numerous national and European projects, methods are developed for areas such as verification, intrusion detection
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17 Mar 2026 Job Information Organisation/Company Linköping University Research Field Computer science Researcher Profile First Stage Researcher (R1) Application Deadline 13 Apr 2026 - 12:00 (UTC
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application! 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
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EuroHPC (Arrhenius) and an AI Factory (Mimer). Cybersecurity research at LiU focuses on securing the most critical functions of digital society. Through numerous national and European projects, methods
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for the position: An established and active research program in Neuroengineering. Deployment of engineering-based methods for development and analysis. Experience of research conducted in close collaboration with
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methods that can accurately model such processes remains an open and active research frontier. This PhD project is fundamentally about advancing that frontier, contributing new methods for generative