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the FORTE Starting Grant: I get by with a little help from AI: Artificial intelligence supported human collaboration. Website: https://www.littlehelpfromai.se/ The project investigates how artificial
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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Programme (semesters 1-5) using various forms of active learning. As a guideline, teaching, educational management and educational development work is expected to account for approximately 70% of the time
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expected to: develop and lead internationally successful research; develop, lead and participate in teaching at first, second and third cycle level; primarily teach small animal surgery, in addition to other
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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learning and simulation-based inference for searches for dark matter (or other “invisible” new physics signals) at the Large Hadron Collider, with the support of competent and friendly colleagues in
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education teaching and learning. The purpose of the position is to develop independence as a researcher and to create the opportunity for further development. The postdoctoral position includes a combination
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dynamics, initially focusing on quantum-inspired techniques such as tensor networks and tensor-network-based machine learning. You will then investigate how these methods can be reformulated and implemented
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high-resolution mass spectrometry, in vitro pharmacological characterisation of new psychoactive substances, as well as metabolomics and machine learning. As a PhD student, you devote most of your time
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includes the opportunity for three weeks of training in higher education teaching and learning. The postdoctoral fellow will: Develop and maintain harmonized satellite time-series datasets (Landsat and