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Generative Artificial Intelligence (GAI) is rapidly transforming higher education, yet most current GAI systems are designed to support individual productivity rather than collaborative learning
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looking for a full-time (100%) doctoral scholarship holder in the field of machine learning for circular polyurethane design. Position You will actively work on the preparation and defence of a PhD thesis
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About the project: Machine learning accelerated Inverse Design of Graphene Nanoribbons for Green Energy Supervisor: Dr Sara Sangtarash, University of Warwick Thermoelectric materials convert heat
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. ● Intervention design and continual learning . Beyond predicting perturbation outcomes: designing interventions that steer cells toward a desired molecular state, and updating trained models as new data arrive
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Are you fascinated by how curiosity shapes learning in the classroom? Would you like to investigate how children seek information, explore and learn in real-world educational settings? If so, then
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representation learning Design reproducible data and experimental workflows for model training, adaptation and evaluation on selected EO applications Investigate MLOps pipelines for reproducible, efficient and
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Statistical methods are leveraged in many scientific applications to: specify a data collection practice (experimental design), draw conclusions from sparse and noisy data (inference), and assess
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. Empa is a research institution of the ETH Domain. In our research group, we design mechanically robust, multi-responsive polyurethane elastomer with backbone-integrated molecular switches. Our aim is to
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learning systems. They will evaluate systems whose behaviour keeps moving, and track, from the inside, whether the structures that carry their capabilities and safety properties hold up under the change. You
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candidate will design algorithms that identify suspicious model updates, reduce the influence of compromised UAVs, and preserve useful learning from honest UAVs operating with different data and unreliable