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of complex dynamical systems. The work will emphasize applications to multi-agent systems, including robotics, autonomous systems, and distributed decision-making. Applicants must have a PhD in
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(nutrition, medicine, food science) and quantitative experts (mathematics, statistics, AI&ML, systems engineering). Supervise, collaborate, and support PhD students and postdocs involved in joint projects
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(e.g. Gibsonian approaches); • Familiarity with theories of cognitive and brain ageing; • Familiarity with theories of synchronisation and complex dynamical systems; • Ability to work independently
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Max Planck Institute of Molecular Cell Biology and Genetics | Dresden, Sachsen | Germany | 24 minutes ago
Applied Algebraic Geometry * Computer Algebra * Data Science / Mathematics of Data * Dynamical Systems and Differential Equations * Information Geometry * Higher Structures and Category Theory * Fluid
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/graduate staff. Where to apply Website https://jobs.energy.imdea.org/en/offer/429 Requirements Research Field Other Education Level PhD or equivalent Skills/Qualifications PhD in Artificial Intelligence
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Mechanical Engineering PhD portal here: https://www.birmingham.ac.uk/study/postgraduate/subjects/mechanical-engineering-courses/mechanical-engineering-phd , specifying the title and main supervisor (Jack
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structures, cluster structures, flat surfaces, and spectral networks. The goal of the project is to build new far-reaching connections between algebraic geometry, dynamical systems, and mathematical physics
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simulations. Experience with dynamical systems theory and mathematical modelling using ODEs and/or DDEs is desirable. What you will get in return: Fantastic market leading Pension scheme Excellent
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for the control, optimization, and coordination of complex dynamical systems. The work will emphasize applications to multi-agent systems, including robotics, autonomous systems, and distributed
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algorithmic and theoretical foundations of reinforcement learning applied to complex, high-dimensional dynamical systems. The project focuses on the intersection of deep reinforcement learning