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Field
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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and planning algorithm for high-speed autonomous vehicle. The work will involve algorithm development, simulation, test rig set-up, and experimental validation. Requirements: The candidate must at least
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to remove PFAS. To accomplish these goals, the candidate will participate in the development of AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross
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Location: Odense, 5230, Denmark [map ] Subject Areas: Pure math with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. Appl Deadline: 2025/12/01 11
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application! We are looking for a PhD student in Scientific Visualization in the scientific visualization group at the division of media and information technologies based at the Department of Science and
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drug experts (clinicians, clinician scientists, data scientists, and laboratory investigators) to co-develop phenotyping algorithms but is expected to serve as the domain expert in high-throughput
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, Mathematical Optimization Cryptography: Post-Quantum Cryptography, Multi-Party Computation, Zero-Knowledge Proofs, Fully Homomorphic Encryption, Privacy-Preserving Algorithms Computer Science & Engineering
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for this role. This role will involve developing and applying analysis plans using a variety of advanced methods with the support of project supervisors. The postholder will have completed a PhD in a relevant
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Apply Now Responsibilities* Conduct research focused on designing and implementing algorithms related to cryo-electron microscopy (cryo-EM) data collection in a lab that focuses on the structural
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to test the current algorithm and inform development of future algorithm refinements aimed at supporting diabetic foot ulcer (DFU) prevention through identification of temperature differences of > 2.2°C