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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
21 Feb 2025 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile Established Researcher (R3
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the ability of neural networks to learn unknown posterior distributions distributions. Their use in the field of image microscopy, however, remains limited. The purpose of this PhD thesis is to develop
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Distributed, robust and adaptive model predictive control (MPC) School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr P Trodden Application Deadline: Applications
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seeking a Regular Title Series (tenure- eligible) Assistant Professor. This position is a 10-month appointment with an anticipated Distribution of Effort of about 45-70% Teaching and Advising, 0% Clinical
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fields for several applications in the field of computer vision and inverse problem [SLX+21]. As far as the modeling of data term between distributions is concerned, one idea would be also to follow
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platforms involving sensors, instrumentation, and physical measurements Involvement in the design, wiring, commissioning, and troubleshooting of systems Collaborate closely with PhD students, postdocs, and
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Research Assistants will work 20 hours per week with flexible distribution. Preferred Qualifications The Graduate Research Assistant position is available to full-time PhD students in good academic standing
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support to the Department of Education and Leadership. Support the Department of Education and Leadership, Associate Dean/Chair, Program Directors, and Faculty. Coordinate survey processes and distribution
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Position Details Position Information Working Title Assistant Professor or Lecturer, Industrial Distribution Brief Summary of Job Description The Industrial Distribution program is seeking
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, and costs of running diverse applications in large-scale distributed systems. This project offers researchers and students a chance to explore cutting-edge concepts in AI-driven infrastructure