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/PhD in Geosciences, Environmental sciences, remote sensing or computational sciences or image vision and related fields Language skills: Excellent English skills, German is beneficial Desirable skills
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architectures for foundation models The work will combine methodological development with large-scale experiments, aiming for contributions at leading machine learning and computer vision venues such as NeurIPS
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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priorities and learn new skills as needed. Office-based role with occasional events requiring evening or weekend hours. Frequent use of computer systems and software, including social media and marketing tools
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Teaching the module M05 Computer Vision & Perception. Developing and delivering module content suitable for online teaching. Providing online resources and learning material for our teaching platform
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experience through research, internships, and industry-sponsored capstone projects. With a versatile curriculum spanning software, systems design, nanofabrication, and machine learning, the program prepares
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Learning has an open position for a doctoral student with a background and strong interest in deep generative learning and computer vision/remote sensing. The successful candidate will join a project funded
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, artificial intelligence, machine learning, and data science. Participate in the mentoring of graduate students, postdoctoral fellows, and staff. Participate in departmental, institutional, and professional
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
conditions, using techniques from computer vision, natural language processing, and representation learning [4,5]. A third objective will be to study how sign-language videos can be represented in a way that
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interdisciplinary degree between Music and Technology degrees (e.g., Electrical and Computer Engineering). Students gain musical training through a musicianship core, applied musical instrument study, and a musical