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development, and computational algorithms A solid understanding of theoretical chemistry and solvation models such as COSMO The ability to work independently as well as collaboratively within a
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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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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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Foundation RECRUIT grant ("Data Management, Algorithms, & Machine Learning for Emerging Problems in Large Networks – with Interdisciplinary Applications in Life & Health Sciences". NNF22OC0072415
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at the department are Algorithms Computational Science Data Science and Statistics Geometry, Topology and Algebra Learning Experience Design Our department offers an inclusive and international working environment
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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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for DATA, Department of Computer Science, Aalborg University, a postdoc position is available. The project is funded by a Novo Nordisk Foundation RECRUIT grant ("Data Management, Algorithms, & Machine
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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