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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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, therefore prior expertise in these topics are highly encouraged: Quantum Machine Learning (QML), Machine Learning on Quantum Computers, Security of Quantum Circuits, Design Automation and Tools for Quantum
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, or similar) will be valued; 9) Experience in machine learning techniques applied to materials science or process engineering (regression, classification, optimization, predictive models) will be valued; 10
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Computer science Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Positions Postdoc Positions Country France Application Deadline 18 Jan 2026 - 17:00 (Europe/Paris) Type of Contract
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departments. This role offers the opportunity to advance AI applications, machine learning, and data analytics to elevate biomedical research, innovate clinical research, and develop next-generation graduate
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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning techniques and generative AI. A strong background in software engineering as well as some
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pangenomics), quantum-based simulation methods for drug design, or quantum machine learning for large omics datasets. The candidate is expected to have acquired first teaching experience, and first experience
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insurance, generous paid leave and retirement programs. To learn more about UofSC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Research Grant or Time