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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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group and are expected to contribute to other departmental tasks. We expect that you have a background in biology or veterinary medicine and have an interest in interactions between diet, intestinal
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supervisors and fellow researchers, you will contribute to the development of solvers for combinatorial optimization problems and apply them to real-world data from industrial partners. As part of your PhD, you
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deformation. Responsibilities Develop scientific machine learning methods in close collaboration with team members specializing in experimental techniques and materials science. Utilize unique experimental data
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simulations.. Qualifications Applicants should hold an MSc in electronics, computer engineering, , Physics, or a closely related field. Required Qualification: Solid background in analog/mixed-signal CMOS
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group specializes in experimental quantum technologies spanning quantum information processing, quantum communication, and precision sensing. In this PhD project, you will work at the forefront of solid
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explored using scientific machine leaning. Machine learning, programming experience and a curious mind-set You are fascinated by how computers can learn from data and you have a strong interest in the
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undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture
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field of social science A demonstrated interest and/or experience in rural, agricultural, and/or environmental issues A high proficiency in Danish, corresponding to C1 or C2 in the Common European
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foods for the future? If you have knowledge within the area of allergy and protein-chemistry as well as have hands-on experience with cell-based in vitro models and are looking for a PhD fellowship