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-based control, the research aims to advance fundamental understanding of friction-driven, limbless locomotion while contributing to next-generation adaptive robotic systems. Research Environment
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, the projects combine classical microbiology, microbial physiology, experimental evolution, and omics-based approaches to link microbial interactions and system performance across spatial and functional scales
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limited knowledge about the benefits and risks of treatment in real-world settings outside the short, controlled framework of clinical trials. In this project, we will combine Danish and Norwegian health
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ongoing national and international research projects and will focus on one or more of the following themes: Artificial intelligence and data driven methods for energy system analysis and control Data-driven
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Job Description A PhD position in inorganic chemistry is currently available at the Department of Physics, Chemistry, and Pharmacy. Project Background Modern industry is heavily reliant on molecular
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analogous neural circuitry and shared molecular pathways have established songbirds as the model system of choice for human speech learning and fine motor control in general. The PhD candidate will use
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languages and platforms (e.g., C/C++, Python, real-time operating systems). Research experience in artificial intelligence, real-time control systems, or adaptive system architectures. Familiarity with
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spring 2026. The position is associated to the ERC Synergy project RECLESS (Recycling versus loss in the marine nitrogen cycle: controls, feedbacks, and the impact of expanding low oxygen regions