18 electric-machine-design-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions in Sweden
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20 Sep 2026 Job Information Organisation/Company Uppsala universitet Department Uppsala University, Department of Electrical Engineering Research Field Engineering » Electrical engineering
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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with nuclear fuel modelling, machine learning
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The Faculty of Engineering and Health Sciences provides education and conducts research in engineering, health and information design, with a clear focus on addressing societal challenges. Our
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the field of Machine Elements. The main aim of this PhD student position is to strengthen the newly started research on Triboelectrictive nanogenerator (TENG)-based smart lubrication in Machine Elements
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. At the Division of Systems and Control , we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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, and increasing data complexity, as well as how monitoring approaches can be designed to remain effective across different marine contexts and scales. The successful candidate will contribute
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entrepreneurship and innovation. Gender, diversity, and inequality in entrepreneurship, including differences in entrepreneurial careers, access to resources, and financing. Meanings and implications of ownership
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modeling of protein dynamics We are seeking a highly motivated PhD student to join a DDLS-funded project at the interface of structural proteomics, protein biophysics, and machine learning. The position is