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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals
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This is a full-time (37 hours/week) on-site role located at Åbogade 34, 8200 Aarhus N, Denmark for a Postdoctoral Fellow at the Department of Computer Science, Aarhus University. The postdoctoral
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algorithms aimed at predicting pathogen potential based on whole or partial genomes. You will also be responsible for integrating such tools into online accessible pipelines thus, providing the possibility
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developed. You should be highly qualified in: Thermodynamic theories and models for electrolyte solutions Mathematical modelling and computational algorithms Scientific dissemination As a formal qualification
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. The candidate will design models and algorithms for learning and decision-making under uncertainty, optimized for real-time operation on heterogeneous physical devices. Finally, the position will address how
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systems, integrated sensing and communication, and theoretical modeling of 6G systems Solid mathematical background and significant experience in scientific computing programming (MATLAB, Python, C/C
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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. Experience with phase retrieval algorithms, clean room use and e-beam lithography are beneficial. The candidate will be expected to participate at international user facilities and thus will be expected
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to ensure that the developed notations and algorithms address the companies’ needs. More about the related project can be found here: https://innovationsfonden.dk/da/news-article/ai-skal-forudsige-og-forklare
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advanced modelling, data analysis, and algorithmic development. Your tasks will support our core research focus of mathematical and computational approaches to design and implement solution algorithms, with