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Field
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) explores the interactions between science, technology, society, and policy, with a distinct focus on the social studies of the life sciences and biomedicine. The group is based at the STS Department
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16 May 2024 Job Information Organisation/Company TU Dresden Research Field Computer science » Computer architecture Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1
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GESIS - Leibniz Institut für Sozialwissenschaften | Mannheim, Baden W rttemberg | Germany | 4 days ago
Programme? Not funded by an EU programme Reference Number SDM-166 Is the Job related to staff position within a Research Infrastructure? No Offer Description GESIS – Leibniz-Institute for the Social Sciences
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postgraduate degree programmes in four multidisciplinary faculties: Technology and Bionics, Life Sciences, Society and Economics, and Communication and Environment. International collaboration is a strength of
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addition to technical models allowing to assess technical scaling and an optimal operation. The optimal plant design is identified by considering the energy supply system, the choice of capture technology, the DAC
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H2 profiles in collaboration with our modeling department Your Profile: MSc in meteorology, physics, chemistry, environmental sciences or a related field with good final grade (German system equivalent
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Developing innovative technology solutions and bringing them to application - that is our goal at the Fraunhofer Institute for Photonic Microsystems IPMS. With our expertise in the development
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Developing innovative technology solutions and bringing them to application - that is our goal at the Fraunhofer Institute for Photonic Microsystems IPMS. With our expertise in the development
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in order to protect the climate. Do you have a passion for quantitative analysis and would like to use computer models to analyze projects such as Longtermscenarios looking at how climate goals can be
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social research or a completed academic degree in empirical social research with knowledge of data science or a related field Very good programming skills in R Very good knowledge of estimating regression