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Field
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seeks to develop innovative computational techniques and theoretical insights that extend the frontiers of both fields. It focuses on leveraging recent breakthroughs that combine algorithmic approaches
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universities, internationally recognized for high quality in research and education. As a societal institution, we shall contribute to sustainable and democratic development and be an attractive and inclusive
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We are seeking a highly motivated Research Fellow to join the project of ‘Development of an AI-based integrated system for safe management of ammonia fuel in maritime sector’ led by Prof. Yang
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and data analytics; Development of marine geophysical survey and machine learning algorithms; Process geophysical/geomechanical data and analyze the data using machine learning; Conduct research
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monitoring including geohazard detection such as sinkhole and subsidence. Key Responsibilities: Develop algorithms for passive seismology, seismic noise analysis, geophysical imaging, and seismic source
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identification through lab-scale and field experiments. Key Responsibilities: Develop algorithms for guided-wave analysis, response analysis, sensor fusion, and system identification using distributed and multi
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the Department). The position is part of the ERC Advanced-prosjektet «New Horizons of Parameterized Complexity» (NewPC). About the project/work tasks The project aims to develop multivariate algorithmic and
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lead the design, statistical optimisation and validation of assays for clinically relevant bladder cancer targets. Their central objective will be to develop an algorithmic workflow to detect new target
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. The position is part of a collaborative project with the University of Edinburgh and the University of Oxford focused on developing scalable methods for complex trait analysis using ancestral recombination
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supply chain processes, including transport operations, fleet management, and operational readiness frameworks Model & Algorithm Development: Design, build and implement optimisation models for various