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This PhD asks a different question: instead of demanding more data, can we build language models that learn smarter from less? You will design AI architectures that adapt to the structure of a
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PhD, you will: perform large-scale potato experiments using 100 contrasting soil microbiomes; use automated high-throughput phenotyping to quantify plant growth, physiology and disease development
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UiO/Anders Lien 4th October 2026 Languages English English English 3-years PhD position in probabilistic machine learning and statistics Apply for this job See advertisement About the position We
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compositionally complex recycled steels, using density functional theory and machine-learned interatomic potentials, in close collaboration with leading academic partners and Tata Steel. Job description At TU Delft
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The continuous release of Earth Observation (satellite) data and the emergence of Machine Learning methods open up new possibilities for understanding forests. These large datasets provide
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perform both empirical and theoretical work. You will learn how to collect and analyse data within your research area as well as communicate your results at national and international conferences and in
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of offers available1Company/InstituteDepartment of Computer ScienceCountryAustriaCityInnsbruckPostal CodeA-6020StreetTechnikerstraße 21 a Contact City Innsbruck Street Technikerstraße 21 a Postal Code A-6020
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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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Constructor Technology, invites applications for a PhD position in machine learning for software engineering and formal methods, on the Constructor Fabric project. Constructor Fabric turns a company's informal
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mapping technologies. This PhD would particularly suit candidates with backgrounds in: Artificial intelligence or machine learning Computer science Data science or computational modelling Engineering