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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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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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team. Significant software development experience in several key languages, e.g., Rust, C++, or Python (not MATLAB), algorithms, and machine learning is necessary as well as excellent communication
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. The work includes theoretical analysis, algorithm design, and validation on realistic case studies, as well as dissemination of results through publications, open-source code, and collaboration with internal
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algorithms for physiological data Development of mobile applications for sensor integration and patient use Support in setting up cloud-based infrastructures for secure data collection and storage
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algorithms for speech enhancement using state-of-the-art machine learning techniques. You will design and evaluate models that leverage phoneme-level or discrete speech representations and conduct experiments
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. The goal is to quantify both the extent of material degradation and its precise spatial distribution within the battery structure. By modeling the battery as a dynamic 3D acoustic landscape, we expect to be
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across Denmark and we want to obtain a basic understanding of their ecophysiology, distribution and importance. The microbes will be selected based on metagenomic investigations (metagenome-assembled