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histories in Central Eurasia by applying palaeoproteomic methods to a selected number of archaeological sites in the region. The position is based in a research group composed of evolutionary and molecular
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simulation tasks. A key objective will be the development and testing of algorithms for gas hydrate phase equilibrium calculations. CapSim seeks to advance CO₂ capture simulation technology by enhancing
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and embedded cryptography, and quantum programming languages. The section is part of the Department of Mathematics and Computer Science, and other research sections at the department are Algorithms
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-evolutionary simulation. The position is available from 1 March 2026 or as soon as possible thereafter and is for 2 years. Qualifications and competences Applicants must have a PhD degree or equivalent or have
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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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predictive framework linking genomic data to extinction risk, working at the interface of evolutionary genomics, simulation modelling, and machine learning. By integrating forward-in-time simulations, real
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environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental sustainability. You will focus on processing
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. You will support field behavioral experiments to test designs of tradable credits schemes in specific urban contexts. You will explore and implement machine-learning algorithms and classical dynamic
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will have the opportunity to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and
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environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental sustainability. You will focus on processing