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enthusiastic scientist with the following competencies and experience: Essential experience and skills: You have a PhD in Machine Learning, Artificial Intelligence, Bioinformatics, Biostatistics, Epidemiology
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, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications include: expertise in programming and coding (preferably using Python and C++) and GUI development
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, FOR ADMISSION TO THE PhD COURSE IN INDUSTRIAL AND INFORMATION ENGINEERING AND ECONOMICS – FOR no. 2 POSITION WITH SCHOLARSHIP: - 1 grant aimed at carrying out research concerning: “Artificial Intelligence (AI
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 8 hours ago
6 Jan 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modelling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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research group under the national competitive funding programme “My First Research Team” . This programme is designed to accelerate the transition to research independence and to support the development
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, implemented under the National Programme for Research, Innovation and Digitalization for Intelligent Transformation (ПНИИДИТ 2021–2027), co-funded by the European Regional Development Fund (ERDF), European
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to enroll in a PhD program Preference will be given to candidates with knowledge and skills in the following areas: machine learning and neural networks, including LSTMs and explainable artificial
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Areas: computer science; applied math; artificial intelligence; machine learning; statistics; engineering Appl Deadline: 2026/02/06 11:59PM (listed until 2026/06/19) Fellowship Description: Apply
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gravitational-wave astronomy. The successful candidate will join Greg Ashton’s STFC-funded programme, Advancing Gravitational-Wave Astronomy Using Artificial Intelligence, to work on computational Bayesian