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listed as the strongest German business school for research, and #9 in Europe for M.Sc. programs in entrepreneurship. The TUM Campus Heilbronn is a dynamic organization whose goal is to achieve excellence
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schools. Professor Hutzschenreuter intensively supports you on your research project. You will work along a structured project plan with clear milestones for each semester. As part of the doctoral studies
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engineering, or geodesy with a specialization in Deep Learning, or in a comparable thematically appropriate discipline. In-depth skills in programming and working with Deep Learning methods. Expertise in
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cooperations efficient and productive. As Research Associate you will also support our teaching activities in several Bachelor and Master programs offered by the School of Engineering and Design and the School
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understanding of business and marketing concepts is essential. Good programming skills in at least one programming language e.g., Python. Experience with machine learning or LLM methods will be a plus. Enthusiasm
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research in the area of entrepreneurship and family enterprise while participating in the doctoral program. TUM School of Management at TUM Campus Heilbronn invites applications for a Research Associate (m/f
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essential. Good programming skills in at least one programming language (e.g., Python). Experience with machine learning, LLMs, or HCI/user study methodologies will be a plus. Strong interest in acquiring and
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public service. • Knowledge in and practical experiences with programming (e.g., Python, Java, Julia, etc.) • A strong interest in scientific research with the goal of obtaining a doctoral degree • High
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will soon obtain the degree are also welcome to apply) - strong background in machine learning - proficiency in Python programming - experience with molecular simulations and knowledge of statistical
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should bring a particular interest in digital design and manufacturing technology and systems design. Ideally, you have skills in CAD modelling, geometry processing, and programming, as well as prior