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) English (United States) MY PROFILE / LOGIN > More Search Options Loading... Clear Create Jobalert Apply now » City: Aachen Date: Oct 13, 2026 BT/MT: »Deep learning and machine learning in
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of the 56th Annual Meeting of the Association for Computational Linguistics (ACL), 2018. [4] Neural Machine Translation for Bilingually Scarce Scenarios: A Deep Multi-task Learning Approach [code
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. You’ll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna’s
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research scientists with a proven track record of applying deep learning to solve complex, high-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a
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, demographic, lifestyle, laboratory, medical imaging and, where available, longitudinal patient data. Machine-learning and deep-learning techniques will be developed and compared for cancer-risk prediction
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, demographic, lifestyle, laboratory, medical imaging and, where available, longitudinal patient data. Machine-learning and deep-learning techniques will be developed and compared for cancer-risk prediction
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imaging and longitudinal data. A range of machine-learning and deep-learning techniques will be developed and evaluated for cardiovascular disease prediction and risk assessment. Advanced AI and Decision
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imaging and longitudinal data. A range of machine-learning and deep-learning techniques will be developed and evaluated for cardiovascular disease prediction and risk assessment. Advanced AI and Decision
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Primary supervisor Lan Du Research area Machine Learning Project Background and Motivation The "inverse design" of molecules from analytical spectra (such as MS2, NMR, or IR) is a fundamental
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Primary supervisor Lan Du Research area Machine Learning Project Background and Motivation The "inverse design" of molecules from analytical spectra (such as MS2, NMR, or IR) is a fundamental