27 programming-"the"-"DAAD"-"U"-"IMPRS-ML"-"IMPRS-ML" positions at Aalborg University
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bachelor’s and master’s degree programs within biomedical engineering, medicine, medicine with industrial specialization, biomedical engineering, sports science, public health, and clinical health and
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280 employees, 100 Ph.D.-students enrolled in the Doctoral School in Medicine, Biomedical Science and Technology, and 1,500 students in our bachelors and master’s programs. We hold state of the art
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(mandatory) Experience as main author in peer-reviewed scientific publications (mandatory) Strong programming skills in Python and deep learning frameworks (mandatory) Documented expertise in one or more of
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our vision for a healthier and more sustainable future. We offer bachelor’s and master’s degree programs within biomedical engineering, medicine, medicine with industrial specialization, biomedical
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program. The Integrated Ph.D. stipend is open for appointment from 01.09.2025. The position is for 4 years, and the workplace is in Aalborg. Your work tasks An Integrated Ph.D. stipend is available in
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primarily be in Automation and Process Monitoring on the following program Bachelor of Science (BSc) in Engineering (Mechanical Engineering). This includes knowledge on, e.g., various perspectives and
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, coordinated by Aalborg University and funded by the EU’s Horizon Europe program. The project aims to improve fiber-to-fiber textile recycling across Europe by developing smarter sorting systems, recycling
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expected to take a lead role in teaching at BSc, MSc, and PhD levels. In particular, the applicant will contribute to the teaching and supervision activities in the division, including at the program
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At the Technical Faculty of IT and Design, Department of Planning, a PhD stipend is available within the general study programme Development and Planning. The stipend is open for appointment from 15
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proficiency in relevant programming languages (e.g., Python, C++) and tools such as ROS. Experience in simulation and digital twins, as well as the use of synthetic data for training machine learning models, is