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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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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design
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technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human
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engineering, economics, psychology, computer science, social data science, machine learning, mathematics, and statistics. As a candidate, you should have a high potential for creative and independent research
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Engineering and Materials & Process Engineering. Close collaboration with our neighbouring Departments (Biosciences, Food, Agroecology, Chemistry, Mechanical Engineering, Electrical & Computer Engineering
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closely related field. The candidates must have excellent written and verbal communication skills and be proficient in written and spoken Danish or demonstrate a willingness to learn Danish within 3-4 years
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biology, or analytical workflows. Interest in single-cell analysis, cancer biology, and translational research. Basic level expertise in computational biology (e.g., bioinformatics, machine learning), with
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Job Description If you are ambitious and interested in joining a supportive and dynamic research team working with Operations Research and Machine Learning on an important application look no
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, statistics). Excellent organizational skills and attention to detail in experimental design and data tracking. Working knowledge of machine learning techniques for high-throughput data interpretation