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mathematics, computer science, or a related field, and strong programming skills, to work on biology-informed machine learning for dynamical systems (see project description below). The position is based at
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mechanical engineering sub-disciplines of solid mechanics, manufacturing processes, mechanical systems design, and/or rigid-body mechanics / dynamical systems analysis are sought. The successful candidate will
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mechanical engineering sub-disciplines of solid mechanics, manufacturing processes, mechanical systems design, and/or rigid-body mechanics / dynamical systems analysis are sought. The successful candidate will
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. Combining dynamical systems theory, mathematical modelling, and data-driven approaches, the research will explore how populations change over time in response to ecological interactions, environmental
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Analysis and Dynamical Systems. Applications should normally be made online. Candidates should provide a full academic CV, to which they should append: (i) a research statement outlining their research
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project developing numerical methods to simulate the flow of dense viscous liquids through a deformable granular mush. The project aims to improve fluid-dynamical understanding of how magmatic ore
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-order spreading” and 2.3 “Higher-order evolutionary processes”), aims to develop theoretical and computational models for the study of dynamical processes on networks with higher-order interactions. By
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in ecological modelling, network analysis, dynamical systems, and linking theoretical approaches with empirical ecological data. Ability to work independently while contributing constructively to an
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work on biology-informed machine learning for dynamical systems (see project description below). The position is based at the Department of Computer Science at Aalto University, Finland, within a
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of physical and/or mathematical modelling; Knowledge of differential equations, dynamical systems and/or partial differential equations; Experience in the study of time-modulated systems, dynamic