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The origin of life remains one of the greatest mysteries in science. While many theories have been proposed, no single explanation has yet gained universal agreement. That’s where the PRELIFE
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PhD position - Modelling the emergence of information transfer in prebiotic self-replicating systems
The origin of life remains one of the greatest mysteries in science. While many theories have been proposed, no single explanation has yet gained universal agreement. That’s where the PRELIFE
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large number of distinct but interacting components. To address these challenges, this project aims to contribute to the development of a control theory that is inherently modular, i.e., that allows
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to the development of a control theory that is inherently modular, i.e., that allows for considering components independently. Inspired by so-called contract theories from computer science, such modular control theory
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on media and journalism studies, digital literacy and inclusion, argumentation theory and AI, combining argumentation theory and affect theory to understand the intertwined processes of cognitive information
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PhD Activating Heritage as a Mediator for Dialogue and Belonging in an Era of Polarization (1.0 FTE)
This PhD project examines how heritage can be activated to support dialogue and strengthen connections between migrants and local communities. It addresses key societal questions about how people
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PhD Position: Activating Heritage as a Mediator for Dialogue and Belonging in an Era of Polarization
This PhD project examines how heritage can be activated to support dialogue and strengthen connections between migrants and local communities. It addresses key societal questions about how people
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these challenges, this project aims to contribute to the development of a control theory that is inherently modular, i.e., that allows for considering components independently. Inspired by so-called contract
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theory and real-world policy design. The PhD position is embedded in the Economics, Econometrics, and Finance research programme of FEB’s Research Institute. The project will be supervised by Dr Viktor
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modelling of materials and machine learning. Experience in atomistic modelling (molecular dynamics, density functional theory) and machine learning is important, as well as a strong interest in pursuing