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Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through
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Engineering and Mechatronics. The Proposed PhD thesis topic: “Intelligent Diagnostics of Electrical Machines through AI-Enabled IoT Systems: Design of Custom Embedded Hardware and Protocol-Aware Architectures
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University, Tyndall National Institute, and Seagate Technology, one of the global leaders in data storage and photonics innovation. Four PhD students will be based at ATU Donegal and will join the
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skills and experience: Essential criteria PhD or equivalent (or thesis submitted*) in at least one of the following subjects: Computer Science, Machine Learning, Biomedical Engineering, Medical Imaging
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inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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engineering Engineering » Electrical engineering Researcher Profile First Stage Researcher (R1) Application Deadline 14 Feb 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not
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engineering Researcher Profile Established Researcher (R3) Positions PhD Positions Application Deadline 10 Feb 2026 - 23:59 (Europe/Brussels) Country Poland Type of Contract To be defined Job Status Full-time
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the PhD project. Qualifications: The applicant must hold a master’s degree in Robotics, Engineering Cybernetics, Automation, Mechatronics, Electrical Engineering, Computer Science, Machine Learning, or a
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Interaction / Human-Centred Artificial Intelligence Help shape the future of work. This PhD project investigates how collaborative AI agents can support communication, learning, and shared understanding in blue