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systems such as fuel cells and batteries. Intelligent control and management systems will be designed to enhance efficiency, sustainability, and seamless integration. Developed models and strategies will be
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Additional preferred expertise and experience Experience with longitudinal data analysis and advanced statistical methods (e.g. linear and generalized mixed-effects models, growth curve analysis and structural
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team will be located within a rewarding professional environment with an active community of PhD candidates and postdocs. Duties of the position As a PhD fellow, you will be expected to: Develop your own
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. These models will then be adapted and applied to other ComDisp case studies in the USA, Ecuador, and Turkey. The PhD candidate will be responsible for: • Developing, testing, and analyzing hybrid simulation
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for: • Developing, testing, and analyzing hybrid simulation models. • Integrating empirical health data with computational models. • Collaborating with research partners in Vietnam and other ComDisp teams
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. The project requires knowledge of real options analysis, quantitative modelling skills and understanding of the CCS value chain. The aim of the project is to: Develop methodologies to assess investment
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and develop frameworks and knowledge on planning and coordination of resources within and across projects. apply quantitative methodologies, such as simulation and analytical modelling, to develop
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statistical methods (e.g. linear and generalized mixed-effects models, growth curve analysis and structural equation modeling). Familiarity with the opioid and endocannabinoid system and topics related
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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://www.ntnu.edu/ept ) at the Norwegian University of Science and Technology (NTNU) is seeking a PhD candidate to work within process modeling and simulation of novel zero-emission oxy-fuel combustion CO2 capture