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Infrastructure? No Offer Description The postdoctoral researcher will contribute to the ANR-funded Pi-CANTHERM project, which aims to design, model, and predict the performance of new n‑type organic thermoelectric
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | about 2 months ago
to the development of quantum error correcting codes for bosonic systems. Potential topics include: efficient state preparation fault-tolerant implementation of logical gates design of new bosonic codes design and
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/Qualifications • PhD in microbiology, molecular biology, or related field • Strong experience in bacteriology and molecular mechanisms of pathogenesis • Previous experience with insect models and host
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be in close collaboration with Dr Thomas Eiwegger, Research Group “Clinical Immunology” at the Karl-Landsteiner University, Austria. Key Accountabilities Plan, direct, and conduct specialized research
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, Nantes Metropole and the CNRS, capitalizes our group's expertises and recent results in the fields of NIR dyes and colorless DSSCs.3 More concretely, it aims to design organic dyes belonging
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. Analysis of experimental characterization will be assisted by numerical simulations using in-house multiscale models of solidification. Main Activities Design and development of experiments. Characterization
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. Scientific innovation and interdisciplinary collaborations are at the heart of our activities. The recruited postdoc will join the Development, Regeneration and Evolution team (www.averof-lab.org ) and will
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quality control. * Design and implement the end-to-end analysis pipeline: preprocessing, source reconstruction, depth-resolved (laminar) analyses, and beta burst detection/analysis; produce reusable, well
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fundamental research and industry-relevant innovation. Thee research carried out at IREENA deals with the energy management, sizing and intégration of new energies within applications ranging from decentralized
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, funded by the ITMO Mathematics and Informatics for Cancer program, is to efficiently process and analyze hundreds of thousands of RNA-seq datasets on human cancer. The central innovation of the project is