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on developing AI algorithms (especially for training) aimed at post-digital hardware. Specifically, the project targets numerical and local learning algorithms beyond backpropagation. Key Responsibilities
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the project leader in the research project - “GNSS/5G/LEO Joint direct positioning: theoretical modelling, algorithm development, and performance evaluation in city areas”. Qualifications Applicants should have
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/hardware development in robotic systems operating under uncertainty. The role will focus on designing, implementing, and experimentally validating advanced algorithms in uncertainty-aware robot perception
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information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care
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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 2 days ago
of numerical optimization algorithms. Software maintenance and development. Read scientific reports. Write scientific reports. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-10548
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stakeholders to translate research into practical tools and workflows. Responsibilities: Develop new concepts and algorithms in data science, machine learning, and artificial intelligence for urban intelligence
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of: Implement and evaluate existing algorithms for the analysis of intra-species strain variability in the oral microbiome. Contribute to the development of novel pipelines to resolve strains in metagenomes
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-enabled scientific workflows that address high-impact national challenges. Responsibilities include, but not limited to: Develop novel AI, machine learning, and knowledge-guided learning algorithms
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NTU’s global reputation for excellence in robotics and AI. Key Responsibilities Design and implement VLA models and world models. Develop and optimize deep learning algorithms to enable robotic arms
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justice, health equity, education, workforce development, or technology governance. Familiarity with applied case studies involving algorithmic bias in areas such as healthcare, hiring, education, finance