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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 22 days ago
skills Specific Requirements The candidate must hold a PhD in machine learning and have strong mathematical skills. Knowledge of bandit models is a plus. LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood
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and innovative learning initiatives. Senior Assistant Professor A PhD or equivalent doctoral qualification in a relevant discipline. Demonstrated track record of research excellence and sustainable peer
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Publish high-impact research in leading journals and present findings at international conferences on energy systems and machine learning Collaborate with industry partner to tackle challenges of practical
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Infrastructure? No Offer Description The PhD candidate will work on the development of advanced statistical and machine learning methods for time series prediction, with applications mainly in the field of traffic
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Machine Intelligence (CVI²) research group (CVI² Group ), led by Prof. Djamila Aouada, to pursue a PhD in Computer Vision with a focus on Media Forensics and Deepfake Detection. The candidate will conduct
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demonstrated experience of writing technical reports. *Candidates must demonstrate an awareness of equality, diversity and inclusion agenda. Desirable: *PhD in machine learning, artificial intelligence, data
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a PhD in machine learning, math, stats, physics, or some other technical area by the time the position starts. Additional Qualifications Candidates should have significant experience in some area of
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Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition; and (iv) Distributed Systems and Networking. These key research areas have a special thematic focus on (a
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and take ownership of work Interest in AI, machine learning, image/audio processing Where to apply Website https://www.timeshighereducation.com/unijobs/listing/408369/research-engineer-r… Requirements
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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