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Job Description We invite applications for a fully funded PhD position focused on the development of advanced computer vision and machine learning algorithms for detection and identification
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-transpositions (plastys) and suture practices for surgical procedures. The specific PhD-project aims at developing efficient hyper elastic-based topology optimization algorithms that take into account skin
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, monocular depth estimation, and reinforcement learning. You will develop innovative algorithms that empower aerial robots to actively explore unknown, unstructured, and GNSS-denied environments while
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of Europe’s ‘green transition’ to clean energy. You will work on cutting-edge research tasks, with objectives including • new algorithms and strategies to improve autonomous Airborne Wind Energy (AWE) operation
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and automated catch registration to advance commercial fisheries. The team is developing fish detection and species identification algorithms, with the goal of implementing the software in
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and thermophysical properties. Furthermore, the group excels in development of efficient phase equilibrium calculation algorithms for compositional simulations. The project is supported by a robust
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candidates in any field of machine learning theory, algorithms and computation or in AI applications in e.g., the social, neuro, or natural sciences, are encouraged to apply. The position comes with a start
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goals Teach and co-supervise BSc and MSc student projects Participate in Arctic field campaigns We expect you to have: Experience in working with large data sets and development of algorithms. At least
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across the value chain. Using Bayesian Optimization / Modern Design of Experiment, we build the data-foundation to enable true hybrid development between humans and advanced learning algorithms such as
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have the opportunity to engage in pioneering research, collaborate with a dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies