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modern cybersecurity requirements. Across both projects, the goal is to combine advanced power-electronic control with edge computation and ML so converters and drives can continuously learn from operation
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contribute to high-impact research on machine learning related to the analysis of IoT data in the form of multivariate time series. The DESS group is part of Department of Computer Science that belongs
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collaboration with industrial and academic partners; access to advanced RF laboratory and high-performance computing facilities; and active contributions to publications, grant applications, and broader project
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Science in Engineering and around 825 students are enrolled in our study programs. Furthermore, we also offer an ambitious PhD program. Our PhD students have high academic ambitions and deliver high-quality
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communication, microwave engineering, and applied AI. Our research combines strong theoretical expertise with unique experimental facilities, including advanced RF laboratories and high-performance computing
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Copenhagen Business School
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
pests, or high-throughput phenotyping Solid background in mathematics and scientific programming (R, Python, etc.) along with effective logical reasoning skills Experience with high-performance computing
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QGG - Aarhus University seeks a postdoc researcher in sustainable breeding: developing simulation...
more than 20 countries. We perform basic and applied research within plants, livestock and human quantitative genetics. Our focus areas include quantitative genetics, breeding plans, artificial intelligence
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DTU Tenure Track Researcher in Experimental High Pressure Phase Behavior for CO2 Storage and Othe...
to the development and improvement of experimental methods and measurement techniques in this field. High-pressure phase behavior and thermophysical properties are essential for the reliable design and safe operation
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and safe operation of CO₂ storage and other sustainable high-pressure processes. In geological CO₂ storage, properties such as phase equilibria, density, and viscosity govern injection performance