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more circular use of carbon resources? In this PhD project, you will explore innovative light-driven strategies for the chemical recycling of polymers. By harnessing the unique reactivity and precise
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system configurations, experimental setups and operational data. The scientific ambition is to develop methods that combine physical models and data-driven approaches for adaptive, real-time operation of
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Are you interested in the long‑term consequences of climate change and adaptation choices and the role that insurers and other financial institutions? Do you want to develop macroeconomic models
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stakeholders. Ability to manage in a scientific environment with in depth knowledge of the different models of research operations while enhancing a collaborative approach. Knowledge of the National Research
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. Knowledge of renewable energy systems (hydropower, wind, solar) and their grid integration. Experience in mathematical modeling, optimization algorithms, and data-driven methods. Possess a strong academic
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modelling for conversion and sorbent regeneration, in conjunction with another PhD student in the department who will perform CFD modelling and other researchers performing process system modelling within
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, theoretical computer science, or a closely related field. Strong enthusiasm for mathematics and abstraction, matched with the motivation to conduct theory-driven research, the ability to develop rigorous
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Department of Spatial Economics The Econometrics and Data Science department aims at pushing the academic frontier in methodology development for quantitative, statistical modeling of data, ranging
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wave equations. In the project, we will develop a new mathematical and computational framework that combines PDE-based modelling with ideas from data-driven reduced-order modelling. The aim is to obtain
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design rules to understand their chemistry and physics. You will combine coarse-grained and atomistic simulations with surrogate models and experimental insights (with Dr. Baumgartner) to understand