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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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background in bioinformatics, machine learning, single-cell omics, statistics, or genomic medicine, and a keen interest in obesity, diabetes, and cardiovascular disease. Background The Novo Nordisk Foundation
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a postdoc in the field of machine learning and decisions applied in cooling systems as per
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: Operator Algebras, Machine Learning, Analytic Number Theory, Automorphic Forms and Representation Theory Appl Deadline: 2025/10/10 11:59PM (posted 2025/09/10, listed until 2025/10/10) Position Description
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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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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: https://ece.au.dk What we offer The Department of Electrical and Computer Engineering offers: An exciting opportunity to work on cutting-edge research in IoT systems and critical infrastructure monitoring
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Post Doctoral Researcher in Human-centred Large Language Models for Software Engineering, Departm...
Engineering can be found here: https://ece.au.dk/en/about-the-department Follow us on our LinkedIn. What we offer The department offers: a well-developed research infrastructure, laboratories and access
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human