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partners. Who we are looking for The following requirements are mandatory: A doctoral degree in mechanical engineering, mathematics, physics, computer science, or a relevant field of fluid or structural
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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Mathematics and Computer Science, Department of Information Technology Are you interested in working with machine
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candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description Quantitative analysis of lipid nanoparticles (LNPs) using Cryo EM is challenging due to heterogenous samples, lack of training data and sample variability. In this project we aim to develop AI/ML...
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AI-driven decision making. It will be conducted in collaboration with the Automatic Control group (from Department of Electrical Engineering) and the Mathematical Optimization group (from Department
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mathematical models, writing scientific papers in collaboration with the project group and external collaborators, and presenting research result at seminars and conferences. Your profile In order to qualify
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Engineering » Other Mathematics » Applied mathematics Technology » Energy technology Researcher Profile Recognised Researcher (R2) Application Deadline 15 Aug 2026 - 21:59 (UTC) Country Sweden Type of Contract
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leave of absence. The research tasks require a solid mathematical background with proven advanced experimental capabilities and excellent programming skills (e.g. C++, ROS, Matlab, etc.). You should have a strong
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if there are special grounds, for example, different types of statutory leave of absence. The research tasks require a solid mathematical background with proven advanced experimental capabilities and excellent
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considered if there are special grounds, for example, different types of statutory leave of absence. The research tasks require a solid mathematical background with proven advanced experimental capabilities