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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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thesis project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer
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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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predictive framework linking genomic data to extinction risk, working at the interface of evolutionary genomics, simulation modelling, and machine learning. By integrating forward-in-time simulations, real
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researchers to gather necessary information and carry out assigned tasks efficiently. DIEM - Digital Entertainment Machine is a research project that explores how ordinary people use digital entertainment in
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algorithms for speech enhancement using state-of-the-art machine learning techniques. You will design and evaluate models that leverage phoneme-level or discrete speech representations and conduct experiments
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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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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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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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to have a strong interest in data analysis, and medical research, along with relevant academic background and skills within medical image analysis and machine learning that will enable them to contribute