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but not essential. A strong background in materials science and/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition
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DTU Management’s Management Science division. The project is led by Professors Stefan Ropke and Richard Lusby and involves international collaboration with leading researchers in machine learning and
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computer science and information system engineering while collaborating in a publicly funded research project with our industry partner Encevo. In this project, the aim is to analyze and build a robust anonymization
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from the chromosome-level reference genome alignments. Historical and population comparisons will also be undertaken. This PhD position will be associated with the Ecology and Animal Science, Production
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to doctoral studies, the applicant must have basic eligibility and have completed a degree in engineering/master's degree in computer engineering/computer science or equivalent, completed course requirements of
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to doctoral studies, the applicant must have basic eligibility and have completed a degree in engineering/master's degree in computer engineering/computer science or equivalent, completed course requirements of
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Current reseach is in the areas of: Development of biomimetic structures as ultrasound contrast agents Deep tissue imaging using photoacoustic contrast agents All optical photoacoustic sensors for tomagraphic imaging in tissue Neural network correction of distortions in acoustic transducers web...
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will be for a 3-year period without teaching. The start date is set for fall 2025, though this is flexible. via Unsplash Qualification requirements A 2-year (120 ETCS) MSc degree in a relevant program is
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fields: Robotics Computer Science Electrical and Computer Engineering Mechanical Engineering Applied Mathematics Applied Physics Statistics and Optimization A strong background in robotics, machine
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characterization aspect of the project, i.e. investigation of dynamics during catalyst activation and reaction by in-situ transmission electron microscopy. VISION is pioneering technology for visualizing catalytic