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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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                will develop algorithms and methods aimed at better detection and mitigation of GNSS interference events from either jamming or spoofing attempts. In addition to research within GNSS integrity 
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                obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. Furthermore, the postdoc will aid in 
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                obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. This postdoc position will utilize 
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                the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. The postdoc will be part of the Microbial Metagenomics group 
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                , number theory, mathematical aspects of quantum field theory, mathematical aspects of string theory, general mathematical physics or quantum algorithms and quantum software development. We stress 
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                , the candidate will be leading the building of a database to i) guide neuroethological studies (behaviour and physiology) in honeybees at University of Konstanz, and ii) train algorithms aimed at modelling and 
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                -disciplinary involving algorithmics, stochastic optimization, multi-criteria decision making, and data science. As part of the project, you will implement and test algorithms and further develop your skills in 
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                . The candidate will collaborate closely with team members to develop novel quantum computing algorithms that leverage hybrid detection methods and explore the potential of 3D cluster states for enabling fault 
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                side, you will investigate and develop data-driven methods for optimal and nonlinear control with a particular focus on dual control and on approaches to measurement scheduling and active sensing