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contrastive learning) and knowledge-distillation strategies from existing foundation models. Curates, preprocesses, and harmonizes multimodal data (structural and functional MRI, PET, EEG, and clinical
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hydraulics. B.Eng. in Civil Engineering. Knowledge of depth averaged modelling of river flows (TELEMAC), knowledge of GIS. Other Qualifying Skills and Abilities: Ability to use scientific instruments and
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Advanced Experience Experience implementing novel machine learning architectures and emerging AI methodologies. Knowledge of multimodal modeling approaches integrating imaging, clinical, and genetic data
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, investigating efficient adaptation strategies and the use of domain-specific data and knowledge. Develop new tabular foundation-model approaches where existing pre-trained models are insufficient, with a
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• Possess a PhD in a related discipline (transportation engineering, operations research, computer engineering/science, or related disciplines) by December 2024. • Strong knowledge and
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of Basel. It contributes to a better future in meeting health care needs through innovative biomedical research and engineering solutions, translating basic science into medical knowledge and healthcare
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Help build the model library at the heart of UTOPYS, a new national facility for real-time power system simulations. Job description Future power systems are converter-dominated, fast, and
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, such as cohort and case-crossover studies. Experience with Bayesian hierarchical models and associated software. Knowledge of the interface between climate science and health impacts, and ideally knowledge
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Specification / Data Science / Computational and/or equivalent combination of education and experience. Knowledge of basic and multivariable statistics. Experience with a range of statistical modeling (e.g
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model utility Unlearning as an AI safety primitive — exploring how federated unlearning can contribute to removing hazardous or harmful knowledge from collaboratively trained models, positioning the work