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next generation of scientists and build a workforce equipped with expertise in integrating advances in biomedical engineering, technology, and Artificial Intelligence (AI) and Machine Learning (ML
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Project Overview We are hiring highly motivated and talented Postdoctoral Associates who are interested in advancing the state of the art in resource-efficient machine learning at the Singapore-MIT
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the
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with the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The research group on statistical models
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an excellent work ethic and background in molecular simulation and machine learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in
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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in
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broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes
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23.02.2026 Application deadline : 30.04.2026 The Autonomous Systems Lab at the University of Tübingen is searching for a Postdoctoral Researcher in machine learning (m/f/d, E13 TV-L, 100%) limited
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Postdoctoral Research Associate will be responsible for AI-driven materials discovery. The position will collaborate with interdisciplinary teams to develop integrated molecular simulation and machine learning
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and