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boundary layer methods (Kármán momentum integral method) • Numerical methods for partial differential equations • Iterative solvers for linear systems • Fluent programming in Python and/or C
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closely related field. Documented experience in energy-system modelling, mathematical optimization, control, digital twins, or related areas. Strong programming and numerical modelling skills using Python
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Python programming skills to implement and prototype research ideas. • A solid mathematical foundation to support the design and analysis of algorithms and systems. • Curiosity, motivation, and the
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Assistant Professor in statistics for the development of privacy-enhancing techniques in health care
modelling. You are required to have: Experience with statistical modelling Strong programming skills in one of the main languages (e.g., R or Python) Proficient in English It will be considered an
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contributing to the management of international projects. Spoken Danish is an advantage, but it is not a requirement. Read more here: https://www.staff.aau.dk/inclusive-recruitment-n64477 Who we are The
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encouraged to apply for the position. Aalborg University has a policy of parallel language use. International staff are encouraged, with support from the university, to learn Danish during their employment
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activities and external funding applications together with colleagues from thermal engineering and power electronics. In parallel with the modelling activities, you will contribute to experimental work at
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individuals, communities, and cultures that make us who we are. We’d love to have you join us! Read more about the department here: https://www.en.bio.aau.dk/ Qualification requirements Appointment as
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application deadline is Monday, November 9, 2026. Interviews are tentatively planned for December 10, 2026. The positions are hosted within the Natural Language Processing (NLP) research group https
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personal background and orientation, is encouraged to apply for the position. Aalborg University has a policy of parallel language use. International staff are encouraged, with support from the