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and high-performance computing resources. The positions are part of the AI RF Sensors research group, which develops AI-driven methods for RF, microwave, and wireless technologies in close collaboration
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ecological communities reassemble under extreme and unprecedented disturbance regimes. A core goal is to identify the key traits that govern colonization, stress tolerance, and ecosystem functioning in post
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A vibrant interdisciplinary environment integrating machine learning and sustainability science. Access to high-performance computing resources and open-source datasets. Opportunities to co-supervise
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1, 2026 (or as soon as possible thereafter) for 12 months initially, with the possibility of extension up to three years based on performance. The successful candidate will investigate gene regulatory
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regulation, or aging biology Interest in applying AI to biological systems and contributing to data-driven hypothesis generation Experience with Linux-based computational environments or high-performance
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job 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
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determination methods (X-ray crystallography and single-particle cryo-EM) and a high-performance GPU computer cluster for structural biology. Your profile The successful candidate should have: A Ph.D. degree in a
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that demonstrate the ability or potential to produce high quality research outputs and publish in international journals A personal research plan which is consistent with the Department of Communication and
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of the chemicals on droplet stability. You will be responsible for the following: Implementing AI imaging to analyze high-speed droplet movies. Relating the results to the HLD principle and performing its parameter