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. Expertise in either computational biology (e.g., bioinformatics, machine learning) or experimental proteomics, with a strong willingness to learn the complementary skill set. Experience in collaborative
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about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its
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Kontogianni. Our research explores how intelligent systems can perceive, understand, and interact with the 3D world. We develop new methods in computer vision, machine learning, and multimodal 3D
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, Biomedical Science and Technology, and 1500 students in our bachelors and masters programmes. We hold state of the art research and we offer state of art learning opportunities in our teaching facilities
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with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs, recovery of dual-comb measurement signals and
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student will become part of a team at DTU with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs
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as well as industrial partners. You will be affiliated with the Section on E-mobility and Prosumer Integration in the Division of Power and Energy Systems. Collaboration with neighboring sections is
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solve problems effectively. Good collaborative skills and a strong interest in participating in an interdisciplinary and international research environment are also highly valued. Approval and Enrolment
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at DTU and other universities as well as industrial partners. You will be affiliated with the Section on E-mobility and Prosumer Integration in the Division of Power and Energy Systems. Collaboration with
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(EoS), or machine learning approaches. Hands-on experience in extracting bioactive compounds from biomass. Strong collaboration skills and the ability to work effectively in interdisciplinary teams. A