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system perform well. This PhD project aims to answer this question. You will develop a unified mathematical theory and framework to study and explain how different reservoir systems work and how to design
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be reduced to mere access to information: it requires mechanisms that foster understanding, sustained motivation, and progressive skill development across heterogeneous populations with different
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methodological approaches Proficient in, or willing to learn, programming languages (e.g. MATLAB, Python, R) Experience with one or more of the following is an asset: LCA tools, computational design, structural
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, they will take an active role in designing and commissioning a pioneering Self‑Driving Lab, a next‑generation autonomous research platform that will integrate Machine Learning and Bayesian optimization
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theory and framework to study and explain how different reservoir systems work and how to design them for specific tasks. The project will combine: Mathematical modelling of dynamical systems
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to the different situations and the benefits or costs that come from the group dynamics. We will moreover compare different types of collective problems (cooperation, coordination…) and investigate if and how global
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in agricultural applications, especially when tested with data that is different from their training setting, even in subtle ways. This studentship is fully funded for 3.5 years from 1st October 2026
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three domains: freshwater, biodiversity, and tree health, each operating within different institutional and policy contexts. Examining these side by side creates an opportunity to better understand how
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project exploring the impact of indoor and outdoor learning environments on children’s language and communication, and how AI can be used to analyse speech and language in this type of research. The project
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through the study plan. To learn more on working as a PhD student at ISY, please contact: isyphdcouncil@groups.liu.se . Starting date by agreement, but earliest in August 2026, and latest December 2026