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characteristics for the aforementioned applications. In particular, resonators capable of generating multiple frequency combs require dedicated investigation. These systems are of central interest for dual-comb
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the "Machine Learning and Gene Regulation" team led by William Ritchie, specializing in bioinformatics and post-transcriptional regulation. The scientific environment at the IGH — international seminars, journal
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demonstrator for a Mott memory nanocrossbar based on the chalcogenide materials GaV4S8 and NiS2. It includes the development of a fabrication process for the integration of innovative nanoelectrodes, as
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Réactions et Génie des Procédés) in Nancy (University of Lorraine – CNRS), within a research environment recognized for its expertise in Process Systems Engineering (PSE) as well as in applied thermodynamics
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-field code, written in the Cuda C language and parallelized on a single GPU (Graphical Processor Unit). A parallelization on multiple GPUs would be a welcome development during the thesis. Where to apply
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7 Mar 2026 Job Information Organisation/Company CNRS Department Laboratoire d'informatique en image et systèmes d'information Research Field Physics Researcher Profile First Stage Researcher (R1) Application Deadline 27 Mar 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job...
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between chemistry and biochemistry. It is structured around two parallel PhD projects: one in chemistry (the position offered) and one in biochemistry, supervised by partner research team. This organization
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metallurgy to produce high‑performance materials through Spark Plasma Sintering (SPS). This process is based on the simultaneous application of high pressure and an electric current through a graphite die
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efficiency Optical neuromorphic computing is emerging as a promising alternative to classical electronic architectures, offering advantages in terms of speed, energy consumption, and parallelism. Nonlinear
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, Interactive and Cognitive Systems, Distributed Systems, Parallel Computing, and Networks. The host team, DAISY, is a joint CNRS, Grenoble INP, and UGA research team handling research challenges