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Job Description DTU Electro invites applications for a PhD position in digital signal processing and machine-learning-enabled continuous-variable quantum key distribution (CV-QKD). The position is
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master's level (corresponding 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
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explore large genomic datasets. Your tasks will include quantitative data analysis, sequence processing and evaluation, and pipeline development and automation. It is expected that you will lead the writing
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research with real industrial practice. You will work on asset-heavy cases from sectors such as energy, manufacturing, and process industries, where maintenance is not just about fixing breakdowns but about
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work experience Other relevant professional activities Curious mind-set with a strong interest in people and nature Good language skills Application and Assessment Procedure Your application including
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within the field of Food Engineering or Food Science that are willing to develop novel membrane separation processes for separation of fat and proteins, as well use a number of techniques for physico and
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(Switzerland). Who are we looking for? We are looking for candidates within the field of Food Engineering or Food Science that are willing to develop novel membrane separation processes for separation of fat and
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qualifications. Possible topics are: The theory of ultrafast pump-probe experiments (e.g., time-resolved X-ray scattering and spectroscopy), simulations and data processing of actual ultrafast experiments, mapping
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the relevant union. The start date is 1 March 2026. The position is part of DTU’s Tenure Track program. Read more about the program and the recruitment process here . You can read more about career paths at DTU
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and qualifications. Possible topics are: The theory of ultrafast pump-probe experiments (e.g., time-resolved X-ray scattering and spectroscopy), simulations and data processing of actual ultrafast