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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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illness. We have a large team working on developing technological solutions for these applications. We are seeking a computer science researcher to take an active role in developing novel machine learning
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 19 days ago
: PD&PEWER Level A&B Postdoctoral - Research Fellow _ CSS.pdf This position will provide opportunities to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited
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, Geography, Civil Engineering, Computer Science, Mathematics, Physics or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning
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for machine learning and artificial intelligence, with a strong emphasis on developing and applying models such as LSTM and other time-series analyses to predict the longevity and behaviour of bioactive
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Laboratory for Artificial Intelligence (the AI Lab) and will receive a competitive salary, benefits, office and equipment, computer resources, and yearly research support. Appointments are for one year with
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of Machine Learning techniques. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase comprises the Academic Evaluation (AC), based
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medical, dental and vision coverage effective on your very first day 2:1 Match on retirement savings Responsibilities* Researching and developing novel machine learning architectures for integration across