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, you design various components of the research. You conduct research that results in a dissertation and aligns with the objectives and requirements of the project. You perform quantitative data analysis
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is expected to be open to combine both positivist and non-positivist approaches under the supervision of Carolin Ischen and Gijs Schumacher, both specialized in large-scale quantitative analysis and
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on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and Data Science, Safety and
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-site, international research project. Your work will include qualitative and quantitative research, development and validation of quality-of-life measures, analysis of risk and resilience factors, and
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engagement. You will have the opportunity to shape the focus of your research according to your background and interests, with an emphasis either on iPSC-based disease modelling or on computational analysis
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the project. Due to the nature of this project, preference will be given to candidates with experience in the reduction and analysis of X-ray, radio or other time-series data, and in scientific programming in
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isotopic analysis for terrestrial paleoecosystems. Until now, only few studies have undertaken this topic, mostly from the archaeological perspective. Other novel approaches include: searching for seasonal
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of flexible hydropower operation on potential internal erosion processes in embankment dams. The research will involve experimental investigations, data analysis, and possible field work, in collaboration with
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in techno-economic analysis and/or life cycle assessment. Research Publications: A record of peer-reviewed publications in relevant scientific journals and/or conference presentations. Personal
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synthesis and characterization. Familiarity with cell culture and in vitro assays. Experience in catalysis, programming and large data analysis is a plus. Excellent communication skills and fluency in English