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state-of-the-art digital technologies such as machine learning Ability to work with other researchers, engineers, and technicians You must be responsible for the teaching of courses. DTU employs two
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theory Machine elements and engineering design Thermodynamics and fluid mechanics This list is not extensive, and applications within the broad field of mechanical engineering are welcomed. We
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engineering. This could for example be within the following topics: Numerical modelling (nonlinear problems, multiscale physics, etc.) Dynamics and vibration theory Machine elements and engineering design
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new analytical and machine learning tools that will help to interpret complex multimodal data, and you will do it in collaboration with top research scientist in the field and in an international
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negative externalities of transport. The division is interdisciplinary with scholars from transportation engineering, economics, psychology, computer science, machine learning, mathematics, and statistics
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, and implementing new analytical and machine learning tools that will help to interpret complex multimodal data, and you will do it in collaboration with top research scientist in the field and in
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independently but supervised by members of the research team. Our expectations of you We seek a candidate with excellent skills using, adapting and analyzing state-of-the-art machine learning models. We seek a
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more than a single semester With strong digital skills and willing to learn more about applying cutting-edge programing language (Computer Vision, LLMs, etc.) As a person, you have good communication skills
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and machine learning in our constantly changing and developing data environment. As our group provides data for many different end-users and projects the work can be very diverse with routine tasks as
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and hands-on experience with machine learning What we offer in return We offer you a varied job with personal challenge, where you greatly help to create a framework enabling isoform analysis. You will