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Molecular Biology, University of Southern Denmark, Odense, Denmark The position is for 3 years and is available from February 1, 2026. Role and Responsibilities Use protein design concepts and deep-learning
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, bioinformatics, aging biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and
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Kontogianni. Our research explores how intelligent systems can perceive, understand, and interact with the 3D world. We develop new methods in computer vision, machine learning, and multimodal 3D
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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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handling robot, and running our Illumina NovaSeq instrument and other instrumentsrelated to NGS e.g., qPCR machine and Fragment Analyzer. In addition, you will be involved in supporting the research projects
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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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Nordisk Foundation (NNF) New Exploratory Research and Discovery grant entitled: Information Theoretic Disentanglement of the Exceptional Biological Learning Machine, which is headed by Professor Jan
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research competence, critical thinking, and disciplinary expertise. Strong expertise in analytical AI and mandatory hands-on experience coding with machine learning frameworks like TensorFlow, PyTorch
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computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics