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of translational research. Good knowledge of the organization and stakeholders of the research ecosystem. Required know-how: Proficiency in common computer tools (use of Word, Excel, PowerPoint, etc.). Proficiency
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of the student lifecycle, from the pre-college programs to career services with a strong focus on admissions and the enrollment process through graduation and beyond, by supporting a connected, comprehensive and
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prototype development, high-value knowledge job creation, and regional economic development through serious game technology discovery to improve the human condition. About the Position: The Project Developer
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Public Notice - International Selection Procedure Recruitment of a Science Manager with a BSc R&D Unit IA, financed by Fundação para a Ciência e a Tecnologia, I.P./MECI FCiências.ID/2026/ IA/1 FCiências.ID
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competitive program that bridges the gap between developmental biology, evolutionary biology, and functional morphology. The emphasis will be on unraveling the genetic and developmental mechanisms underlying
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
), the objective of this internship is to improve the performance of full waveform inversion (FWI) algorithms for seismic subsurface imaging. This work lies at the interface between Earth sciences, mathematics, and
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materials science, structural biology, chemistry and nanotechnology. NanoLund (http://www.nano.lu.se ), formerly known as the Nanometer Structure Consortium, founded in 1988, supports and coordinates
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, industrial and international partners. SnT is active in several national projects funded by National Research Fund (FNR) and local industries, and international research projects funded by the EU FP7 program
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the following education, experience, and skills: Advanced technical knowledge of Linux and/or Windows operation systems Advanced technical knowledge of container technology using Docker images along with
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engineering/M2) to have a solid background in applied mathematics, Machine/Deep Learning, in particular generative models (diffusion models, flow matching), as well as in statistical signal/image processing and