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Università degli Studi di Roma Tor Vergata - Dipartimento di Ingegneria Elettronica | Italy | 2 months ago
7 Jul 2026 Job Information Organisation/Company Università degli Studi di Roma Tor Vergata - Dipartimento di Ingegneria Elettronica Research Field Engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application...
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Temporary Online Microcredential Course Developer- AI Literacy and Policy Fundamentals: Understanding and Mitigating Algorithmic Bias Location: Remote (U.S. based only) Division: Rabb School
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for the position of postdoctoral position (assistant professor) in the NCN OPUS grant no 2024/53/B/ST6/03852 entitled: Algorithmic challenges of molecular evolution. The masculine personal nouns used in
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novel 3D modeling algorithms for near-surface characterization using curated geo-data. Contribute to the development of intelligent geophysical imaging algorithms. Publish high-impact research articles in
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develop novel theoretical frameworks and algorithms for quantum-enhanced learning and intelligent agents, with research directions including quantum advantages in data-sparse learning, quantum algorithms
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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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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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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
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to develop algorithms, metrics, efficient software and visualization tools for the analysis of complex systems with higher-order interactions. The activity will focus on scalable computational methods
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analysis and interpretation of the collected data, with attention to algorithmic gatekeeping, filter bubbles, rabbit holes and ethical research practice; developing a Master’s thesis within the scope