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Field
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, collaborate openly across institutions, and have the stamina to push through the engineering challenges that come with real-world physical AI. Your experience and profile: a PhD degree in Computer Vision
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the neurovascular space. Knowledge of neurovascular anatomy, acute stroke, endovascular treatments, neuroendovascular devices for the treatment of stroke. Ability to generate machine learning analysis of medical
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are looking for candidates who are passionate about applying research to industrial challenges. You will have: Essential: A PhD in materials science, mechanical engineering, manufacturing engineering, or a
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successful in this position, you will ideally bring the following: For the Networking and AI position: Completed a PhD in Computer Science, Electrical & Computer Engineering, or a closely related field Expert
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and automated floor-plan recognition, to fill data gaps and harmonise information from disparate sources. Learn more and watch our project video here: https://sb.chalmers.se/digital-material-inventories
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, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
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experience in the following areas: Knowledge of computer science and machine learning. Familiarity with electrical and electronic engineering. Proficiency in programming languages such as Python, C++
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themes of teaching and research include Digitalisation, Machine Learning, Autonomous and Intelligent Systems, Cybersecurity and Health Technology. The Faculty of Technology is the newest faculty
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Chemical Engineering, Materials Science, or a related field The candidate should have a background in at least one of the following areas: quantum mechanics, molecular simulation, and machine learning
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27 Feb 2026 Job Information Organisation/Company Fondazione Bruno Kessler Department Unità People Innovation Research Field Technology » Computer technology Researcher Profile Recognised Researcher