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) Country Sweden Application Deadline 30 Dec 2025 - 22:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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will work at Campus Solna, located at SciLifeLab, and have access to a dynamic research setting. You will also be part of SciLifeLab and the Wallenberg National Program for Data-Driven Life Science – one
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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conduct world-class applied research. We change and make a difference. Do you want to become one of us? The Department of Computer Science (DIDA) is one of three departments at the Faculty of Computing
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7 Mar 2025 Job Information Organisation/Company Linköping University Research Field Computer science » Other Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Country
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background and interest in static and/or dynamic program analysis, programming language techniques, formal verification, or software engineering, excellent communication skills with sufficient proficiency in
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flow phenomena. The goal is to integrate theoretical and experimental fluid dynamics with modern computational tools to analyze and predict multiphase flow behavior. The project also involves applying
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
professors and a dynamic team of PhD students and postdocs working in areas such as wireless and optical communication, information security, information theory, and machine learning. At the department, we