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Are you an experienced researcher in microbial genomics and bioinformatics with a strong record of university teaching, and expertise in whole-genome sequencing (WGS) analysis, machine learning and
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data integration and analysis Integrate phylogenomic and functional data using machine-learning approaches for candidate gene prioritisation Contribute to software and web-tool development Present
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populations. Apply Artificial Intelligence (AI) methods including deep learning (DL) models and supervised and unsupervised machine learning (ML) methods for integration and for Genome-2-Phenome (G2P) and risk
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populations. Apply Artificial Intelligence (AI) methods including deep learning (DL) models and supervised and unsupervised machine learning (ML) methods for integration and for Genome-2-Phenome (G2P) and risk
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within this field. Your work tasks In this position you will conduct research within Computer Vision and Deep Learning, with a particular focus on the development of an AI-powered framework
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and other postdoctoral researchers as part of our Lundbeck Professorship grant, which you can learn more about here: https://www.cnap.hst.aau.dk/lundbeck-professorship As a postdoctoral researcher your