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opportunity to join the ERC-funded project “ALPS - AI-based Learning for Physical Simulation”. Expected start date and duration of employment These are 1–year positions from 1 May 2026 or as soon possible. Job
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particular emphasis on automated decision-making in autonomous cyber-physical systems. The application areas cover a wide spectrum of autonomous systems, including AGVs/UGVs, UAVs, USVs, and related systems
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physical location of this position will be at the Copenhagen campus of Aalborg University. Job Description This position is part of the cross-disciplinary DK-Future project – Probabilistic Geospatial Machine
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will: Develop and implement model-based and data-driven (AI) optimization algorithms for battery charging Integrate physics-informed models and data-driven tools to design health-aware charging protocols
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questions about the position, you are more than welcome to contact us. You will find contact persons at the bottom of the jobpost. Further information Read more about our recruitment process here
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pH and oxygen (O₂) gradients shape cellular phenotypes and gene regulation in vivo. The position is for 2 years with possibility for extension and will be taking place physically in the Sandelin and
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₂) gradients shape cellular phenotypes and gene regulation in vivo, with a focus on pancreatic cancer. The position is for 2 years with possibility for extension and will be taking place physically in
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@energy.aau.dk Other questions, please contact HR AAU Energy: hr@energy.aau.dk. Further information Read more about our recruitment process here The appointment process at Aalborg University involves a
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to support decision-making by integrating physical models and sensor data. These methods are validated through industrial case studies, with a particular emphasis on critical infrastructures where complexity
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is to use a cutting-edge ensemble of genetic, cell biological, biochemical, organismal, and modern ‘omic’-approaches to achieve a comprehensive understanding of the process of gene expression. CGEN