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or infrastructure. This is what makes our daily work so meaningful and exciting. The Division of Computational Genomics and Systems Genetics is seeking from October 2025 a PhD Student in Deep Learning for Rare
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PostDoc in the project). Collaborating with fellow researchers across the UPLIFT network, including those focused on digital twins at DTU Chemical Engineering- As a PhD candidate, your work will adapt
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%, limited for 3 years, start: as soon as possible) in the trilateral program “Future Proofing Plants to a Changing Climate” (funded by DFG, UKRI-BBSRC, NSF, USDA-NIFA) Who we are: The research group Symbiosis
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of the position: Follow the faculty’s PhD program Plan design and carry out experiments and their analysis Prepare research articles for peer-reviewed journals (min. 3) Be willing to present results at conferences
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emissions from transport. Decarbonising aviation is a vital part of achieving net zero. Hybrid and ‘all electric’ aircraft technologies offer a pathway to net zero. The electrification of aircraft, for both
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and international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking
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structured PhD program with a comprehensive range of continuing education and networking opportunities - more information about the PhD program at the HZDR can be found here Salary and social benefits in
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training programme on Regenerative Agriculture. The requirements to applicants is: You have: Background in soil sciences and agricultural sciences or related field; Experience in process-based modeling
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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each year. Modern applications—from power grids to vehicle platoons—depend on large networks of autonomous subsystems. Without a solid theoretical underpinning, ensuring both collective objectives