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characterization of soft scaffolds with programmed morphological characteristics and tailored mechanical properties. The research will be supervised by Associate Professor Stavros Gaitanaros. As part of the project
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to academic and collaborative research activities in the group and with external partners. You will also contribute to educational activities in bachelor and master programs supported by the group. Your
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, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system-level programming, developing prototype
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writing and orally in academic contexts and to the broader public (Danish is an advantage but not required) Present research results at international conferences Possibly contribute to teaching programs (in
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software skills Proven experience with CFD automation, e.g. using PyFluent or similar Python APIs for meshing, solver control, post-processing and data management. Solid experience programming in Python
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collaborating with clinicians such as orthopaedic surgeons. Strong practical programming skills in Python and/or C++. Ability to manage own academic research and associated activities. Ability to contribute ideas
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relevant to the specific position. Experience with coding and data management in common statistical programming languages (e.g., R, Python, SPSS) or packages for managing and exploring qualitative data (e.g