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Mälardalen University (MDU) is the youngest university in Sweden. In line with our vision, to be a progressive and collaborative University where we shape a sustainable future together, we wish to make a difference. Do you want to be involved and contribute to our development? Together, we can...
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. The Department of Computer Science and Informatics provides academic programmes in subjects ranging from software engineering and embedded systems to user experience design and cybersecurity, and is also
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research, addressing the big data and artificial intelligence challenges of our industry partners. Field of subject for the position: Computer Science Placement: Department of Computer Science and Media
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Computing Science seeks a postdoctoral researcher who will work on Compilers for Linear
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Postdoctoral studies in single-cell and computational biology Do you want to contribute to top quality medical research? A postdoctoral position is available in the laboratory of Professor Francois
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computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher to contribute to our ambitious mission. Division The Division of Biomolecular and
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-of-the-art semantic and instance segmentation algorithms for 3D and 4D microtomography data. The project has a particular focus towards analysing fibre-based materials but will also consider other material
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. The research group is part of the National Program for Data-driven Life Science (DDLS), generously funded by the Knut and Alice Wallenberg Foundation: www.scilifelab.se/data-driven/ Our group focuses on studying
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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description