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to industry, Vanguard has also the mission of developing an ecosystem of related start-ups. For more information about our Center, please visit our webpage: https://vanguard.um6p.ma/ Offer description
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learning algorithms constitutes a very promising research direction for energy-efficient and Edge AI applications: the goal here is to make these systems capable of learning per se, not just inference
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of the discipline, industry and society. For further information about the School, please visit http://www.civeng.unsw.edu.au/ Skills & Experience PhD in a relevant discipline or equivalent experience. Demonstrated
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research in neuro-symbolic AI, with a focus on using generative and agentic AI, as well as AI standards to create trustworthy information resources. This includes the design of algorithms, tools, and process
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Circuits, Robust and Efficient Mapping of Quantum Algorithms on Quantum Machines, Quantum Noise-Aware Optimizations for QML, QML Security, Error Correction for Quantum Computing, Secure Quantum-Classical
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Matter 2022, 10.1021/acsanm.2c03406) we have developed a chemical assay coupled with a machine learning algorithm to measure the impact of wood-aging on a range of foodstuffs. The project involves
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6 Research Professors (DR2). Competitive entry is open for research themes pertaining to Physics M/F
6 Dec 2025 Job Information Organisation/Company CNRS Department CNRS Research Field Computer science Mathematics » Algorithms Researcher Profile Established Researcher (R3) Country France
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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 13 days ago
for matching and aligning anatomical structures Where to apply Website https://umfst.ro/info-studenti/studii/doctorat/cercetatori-postdoctorali/ Requirements Research FieldOtherEducation LevelPhD or equivalent
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Website: https://www.systemshematology.org (link is external) How to Submit Application Materials: Please email Asiri (asiri at stanford.edu) Does this position pay above the required minimum
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scientific imaging (TR-FLIM, HSI, ISM), designing mathematical and unsupervised learning algorithms for nonlinear inverse problems, with reliable reconstructions even with limited data. Where to apply Website