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polarisation shaping, and finally using deep learning to solve the complexity challenge associated with coherent beam combination. The role Within HiPPo, your specific task will be to develop a ‘digital fibre
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). The position is subject to financing by the University of Bergen. About the project/work tasks Geometric Deep Learning (GDL) is a branch of machine learning that develops neural network models by explicitly
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scientific leaders and researchers. Job responsibilities The project aims to advance the use of machine learning techniques to model and understand plasma turbulence in magnetically confined fusion plasmas
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that research delivers against their requirements. Qualifications: APhD in Computer Science/Computer Vision/AI or a closely related field. Extensive research experiencein machine learning, deep learning, and self
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to diverse academic and industrial audiences. Proficiency in Python and deep learning frameworks such as PyTorch. Experience with Linux environments and GPU cluster management is essential. Competent in
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 20 days ago
, financed by EU and national funds through FCT/MCTES (PIDDAC Workplan: Machine learning algorithms, in particular deep learning ones, suffer from the phenomena of catastrophic forgetting, which hampers
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to behavioural and population health data relevant to Singapore’s diverse communities. Develop predictive and explainable machine learning/deep learning/genAI models using multimodal cross-section and longitudinal
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, and who are eager to contribute to impactful methods for generating private and fair synthetic data with good utility. This project involves development of deep learning based synthetic data generators
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Informatics, Health Data Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated
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on artificial intelligence techniques, namely machine learning and deep learning; (3) analysing mathematical models applicable to renewable energy generation technologies and electrical energy storage systems; (4