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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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and two companies. The project has partners from eight different EU countries. All 15 Ph.d. projects are within the overall theme of neuromorphic computing and analog signal processing, targeting
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of neuromorphic computing and analog signal processing, targeting applications in the fields of communication, sensing, geolocalization, space and biomedical. This Ph.D. project will take place at DTU Electro
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Danish master’s degree (two years). Other important criteria are: Professional qualifications relevant to the PhD project Relevant work experience Previous publications The grade point average achieved
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. At that point, the terms of employment and payment will be according to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The
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. This position is part of a strategic research collaboration between DTU and the Korea Advanced Institute of Science and Technology (KAIST), combining expertise in biomedical signal processing, neuroengineering
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for a period of 12 months. Prolongation of the contract is contingent on sufficient progress in the first year to indicate that a successful completion of the PhD thesis within the next three years is to
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to the 3 + 2 Bologna process) have received the grade of 10 (or equivalent) for the master's thesis according to the Danish 7-point grading scale (https://ufm.dk/en/education/the-danish-education-system
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning