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Vacancies Postdoc position on Scalable Energy-Efficient Deep Learning Key takeaways The successful candidate will be involved in cutting-edge research aimed at developing scalable sparse deep
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(large-scale) assessment, such as neurophysiology, extended reality, eye-tracking, psychometrics, and machine learning. About the organisation The Faculty of Behavioral, Management and Social sciences (BMS
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benchmark sparse training methods to scale up deep learning. Publish and present research findings in top-tier conferences (e.g., NeurIPS, ICLR, ICML, IJCAI, AAMAS, ECMLPKDD) and journals (e.g., Machine
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. Publish and present research findings in top-tier conferences (e.g., Machine Learning, JMLR) and journals (e.g., NeurIPS, ICLR, ICML, IJCAI, AAMAS, ECMLPKDD). Collaborate with a international team of
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availability of training data significantly impact the accuracy of data analyses and machine learning tasks. Nonetheless, data is frequently isolated in silos due to privacy issues, legal constraints