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these new large-scale data sources to develop new approaches for analysis of microbial horizontal gene transfer using long-read metagenomics in complex environments. The postdoc will be part of the Microbial
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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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the ERC Starting Grant research project “Exploiting Nanopore sequencing to discover what microbes eat (NanoEat)” with the aim to combine state-of-the-art metagenome sequencing with state-of-the-art data
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to vastly improve our ability to recover microbial genomes from metagenomes. Specifically, we aim to take advantage of the vast amount of high-quality long-read data that is readily obtainable using
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learning methods that leverage the unique properties of SAR data. Develop a foundation model pre-trained on large Synthetic Aperture Radar (SAR) datasets. Demonstrate the practical utility of the foundation
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architectures, and large language models (LLMs) as powerful tools for uncovering, quantifying, and interpreting causal information flow within the brain’s dynamic networks. Your competencies Prospective
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fermentation process to produce large amounts for feeding trials by project partners. The work will be focused around applied microbiology and fermentation technology ranging from lab scale to 100 liter pilot
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challenges at the intersection of AI and cybersecurity, aiming to enhance model integrity, data privacy, and resilience to adversarial attacks. The research will explore methods to secure AI systems in real
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Measurements and Data Processing as per December 15, 2025, or as soon as possible thereafter. The position is available for a period of 1 year, with the possibility of extension. In electronic engineering
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for large-scale data collection and patient interaction. The position offers a unique opportunity to work at the intersection of biomedical engineering, app development, and health data science in a leading