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research experience and are explicitly encouraged (e.g. South America, Asia or Africa). The PhD process will be accompanied by integration into TUM’s School of Life Sciences or School of Management and
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following position in the working group of Evolutionary Analyses and Biological Archives, starting as soon as possible: PhD Researcher in Phytoplankton Parasitoid Ecology (m/f/d) (Part time: 65 %) Location
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The INM research group Structure Formation is seeking for a motivated Doctoral Researcher interested in the self-assembly of nanoplatelets (NPLs) for optical applications. This PhD project is part
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Mainmenu Information for Prospective Students Current Students Staff Teaching Staff Alumni Media Business Lifelong learning Quicklinks All Degree Programs ALMA Portal Excellence Strategy Staff Search (EPV
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the perspective towards generating data for entrepreneurial seed funding (GO-Bio etc.) for a further development of the technology towards the market. In that sense we also highly encourage candidates that would be
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: excellent university degree (diploma, master's degree) in transport or related study programs with a solid basis in transport, data science, and/or data analytics; or equivalent practical experience
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University and at the Heidelberg University of Jewish Studies (depending on PhD supervision), the following positions (65%) for up to 3+1 years are to be filled by 1 April 2026: 12 pre-doctoral research
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available in the further tabs (e.g. “Application requirements”). Objective A cooperation agreement on the joint training and education of PhD students has existed between the Chinese Academy of Sciences (CAS
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of Engineering and Design. Our teaching and research focus lies on computer-based development of engineering products, particularly on the planning and realization of built facilities using computational modeling
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, environmental or natural resource economics) or related disciplines strong analytical (i.e. microeconomics, production or resource economics) and methodological skills with a focus on quantitative data analysis