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Field
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Profile We are looking for candidates who meet the following criteria: PhD in relevant fields: plant sciences, functional genomics, molecular & applied genetics, bioinformatics, artificial intelligence
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: Scientific Area: Data Science and Engineering; Electrical and Computer Engineering; Computer Science and Engineering; Artificial Intelligence; Computer Vision; Computer Science; Data Science; or Mathematical
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, United States of America [map ] Subject Area: Computer Science / Artificial intelligence and machine learning Appl Deadline: 2025/11/21 04:59 AM UnitedKingdomTime (posted 2025/10/23 05:00 AM UnitedKingdomTime) Position
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analysis, product formulation, microbial food, and culinary sciences. Bioreactor design, bioprocess engineering, downstream processing applied to future food Artificial Intelligence and alternative proteins
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Research Fellow will be appointed through the Princeton Laboratory for Artificial Intelligence (the AI Lab) and will receive a competitive salary, benefits, office and equipment, computer resources, and
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Responsibilities Applied Research and Innovation Lead and manage projects focused on product innovation, including, Artificial Intelligence, renewable energy, circular economy, sustainable materials, and carbon
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advanced artificial intelligence techniques to the development of innovative solutions will be highly valued. - The candidate should also demonstrate strong programming skills, as well as expertise in
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reviewed throughout their lifecycle. You will also have the opportunity to engage with PhD students from the UKRI AI Centre for Doctoral Training in Safe Artificial Intelligence Systems (SAINTS) through
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sociotechnical contexts. You will also have the opportunity to engage with PhD students from the UKRI AI Centre for Doctoral Training in Safe Artificial Intelligence Systems (SAINTS) through joint research
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capabilities to aid in the predictive engineering of biological systems, such as proteins, as part of the NIST Engineering Biology Program. Develop artificial intelligence and machine learning analysis pipelines