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Field
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Assistant/Associate Professor of Practice in Human-AI Interaction, Machine Learning, and Data Design
developing, training, and deploying advanced AI, data, and machine learning systems from a human-centered innovation lens. Preference will be given to candidates whose background includes i) experience
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once a suitable candidate is selected. Are you interested in developing machine-learning methods for protein design and applying them to a new class of materials-manufacturing problem? The Research
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looking for a full-time (100%) doctoral scholarship holder in the field of machine learning for circular polyurethane design. Position You will actively work on the preparation and defence of a PhD thesis
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, for continuous and non-invasive health monitoring. Through the development of robust machine learning models, and uncertainty-aware prediction methods, the project aims to improve the early detection of movement
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currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security. As our government customers adopt AI and machine learning to provide leap-ahead mission
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Università degli Studi di Roma Tor Vergata - Dipartimento di Ingegneria Elettronica | Italy | 3 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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currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security. As our government customers adopt AI and machine learning to provide leap-ahead mission
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://www.di.ubi.pt ), under the following conditions: Research Field: Machine Learning/Pattern Recognition Objectives: Foundational Models for Human-Machine Interaction Work plan: The work consists in develop a system
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://www.di.ubi.pt ), under the following conditions: Research Field: Machine Learning/Pattern Recognition Objectives: Unsupervised Incremental Representation Learning for Ground-Based Drones in Dynamic Industrial
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RAP opportunity at National Institute of Standards and Technology NIST Scientific machine learning methods for trustable accelerated materials characterization and design Location Material