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Field
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. Relevant skills could include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool development. Experience in conducting
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, and assist in advising master's students. Your network and team Your doctoral studies and research will be supervised by Associate Professor Arttu Polojärvi. You will work in his team and in close
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its Career Center, Teaching Center, and Office of Postdoctoral Affairs. As part of our vibrant scientific community, you will have access to state-of-the-art facilities and a network of
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Potsdam-Institut für Klimafolgenforschung e.V. (PIK) | Potsdam, Brandenburg | Germany | about 2 months ago
closely with the principal investigator for PIK’s part of the project, Prof. Dr. Elmar Kriegler. Contribute to the development and analysis of sustainable development pathways and international climate
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students, post-docs and project researchers), as well as with an extended network of international collaborators. Job description The selected candidate will be working under the ERC-funded project entitled
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
following areas: High-dimensional probability and concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations
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for interaction and collaboration with faculty and other scholars, both at Yale and beyond. Internal Network: Dr Robert Sanderson – Primary mentor and supervisor Dr William Mattingly – Secondary mentor, assistance
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-powered data analysis to advance hypothesis-driven research related to addiction. Computational analysis of previously collected data can increase the speed and efficiency of life sciences research
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of Experimental Aerodynamics, Computational Fluid Dynamics and Flow Control. The group has a specific expertise in the field of advanced experimental and computational techniques for the analysis of aerodynamic
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production and visual sensitivity, a web-based LCOE calculator, and a multi-criteria decision analysis (MCDA) methodology for comparing candidate demonstrator sites. The project directly supports Action 3 and