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wireless communications systems. For details, you may refer to the following: https://wwwen.uni.lu/snt/research/sigcom We’re looking for people driven by excellence, excited about innovation, and looking
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
retrieval algorithm development with focus on using the polarimetric signals, the new FIR or sub-mm bands, and/or the ML/AI approach; (3) ML/AI application on system/pattern tracking on satellite images
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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conducted implementations of algorithms and simulations using contemporary GPU hardware, or Profound knowledge and experience of the DUNE software environment (https://dune-project.org/ ) (knowledge and
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» Algorithms Researcher Profile First Stage Researcher (R1) Country France Application Deadline 27 Nov 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1
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) Experience in deep learning algorithms is a plus Ability to work in a highly international team and interdisciplinary project applicants are expected to have excellent language skills in English Opportunity
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 26 days 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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computational cognition. The successful candidate will work at the intersection of AI research, cognitive modelling, and human–machine interaction, contributing to the design of algorithms that incorporate
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to source localization based on microphone arrays or distributed sensors. This PhD project will focus on the development of novel methods and algorithms for airborne noise source localization in generic urban
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research on AI/ML methods for accelerating integrated circuit (IC) design. * Participate in the deployment and testing of AI/ML-driven IC design algorithms to both open-source and industry-standard CAD tools