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to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), coordinated by SciLifeLab, aims to recruit and train the next-generation of data
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knowledge of C++ in relation to scientific software. You have acquired one of the two following skill sets (both is a strong merit): Previously conducted implementations of algorithms and simulations using
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, actively participate in scientific seminars, and benefit from opportunities for networking and career development. The place on the programme is linked to a full-time doctoral studentship for the duration
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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 algorithms. Our research integrates
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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 national and international
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principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several national and international research groups, edits one of the major
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the areas listed below. For further details, please contact the corresponding advisor. Applications in other areas may also be considered; inquiries may be directed to David Rydh the head of the Ph.D
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experience in radar research, developing signal processing algorithms for long-range ultra-broadband Synthetic Aperture Radar systems and short-range FMCW systems. In recent years, breakthroughs in
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. The postdoc will contribute to the design and development of next-generation of Low Earth Orbit (LEO) satellite communication systems utilizing extremely-high-rate sub-terahertz (100 GHz – 300 GHz) spectrum
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for efficient quantification of spatial distribution in electron tomograms? Examples of work that you may conduct during your postdoc: Algorithm development and implementation (e.g. in C++). Machine learning