35 physics-engineer-"https:"-"https:"-"Universidade-do-Minho---ISISE" PhD positions at Technical University of Munich
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bridging physics and engineering with chemistry, biology and medicine there are highly diverse opportunities to innovate, collaborate and excel. We support career development, continuing education and
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of helicopter components using a data-based as well as a physics-based approach. In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed in cooperation with Kopter
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measured data Your Profile We are looking for a motivated and independent candidate with a strong background in physics or engineering. Required qualifications: - Master’s degree in Physics, Electrical
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the course of the application process pursuant to Art. 13 of the General Data Protection Regulation of the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By submitting your
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physics, biomedical/material engineering or a related discipline. You have a strong background in data analysis and image processing. You enjoy working in interdisciplinary and international teams and have
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or comparable degree in physics, biology, bioengineering, material engineering or a related discipline. You have experimental experience in cell/tissue culture, microfluidics, or a related discipline. You enjoy
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in the deep ocean and help unravel how life emerged on earth. Requirements As a suitable candidate, you have an outstanding Master's degree or comparable degree in physics or a related discipline. You
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-based fiber materials. Qualification We are looking for a candidate with the following qualifications: Master in Polymer Chemistry, Polymer Physics, Material Science/ Engineering Experience with bio-based
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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Master’s degree in physics, chemistry, materials science, chemical engineering, or a related field who are excited about applying machine learning and data science to real-world materials challenges