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of microorganisms in fluids. Living systems such as bacteria or algae exhibit remarkable capabilities: they swim, adapt, interact, and self-organize into dynamic patterns. Understanding and replicating these life
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dissipative networks. We will view learning as a feedback interconnection of continuous-time (circuit) dynamics and an optimization algorithm. The key idea is to develop algorithms that minimise cost functions
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21 Sep 2026 Job Information Organisation/Company Max-Born-Institute Department T2 Research Field Physics » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application
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Monash/Bayreuth Double PhD Degree Opportunity - Accelerating organic semiconductor discovery with generative AI, molecular dynamics and DFT Job No.: 698040 Location: Clayton (home) and Bayreuth
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systems still face major challenges when operating in fluid environments such as air or water. Unlike ground robots, aerial and underwater robots exhibit dynamics that are strongly coupled with
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) for a multi-component Fe alloy system, enabling predictive molecular dynamics (MD) simulations capable of probing hydrogen diffusion and trapping at interfaces in the presence of tramp elements with near
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. You will be involved in the further development and application of the FlexSem model system, which is a framework developed by the model group to describe the dynamics of coastal marine systems
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Application deadline: 15.11.2026 This PhD will be undertaken over a total period of 70 months and will combine research and teaching responsibilities. This PhD project is fully funded; students who
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part of a new lab at the Delft Center for Systems and Control, supervised by Gabriel de Albuquerque Gleizer. The research will allow you to gain deep insights across nonlinear dynamics, optimization, and
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includes an extension of up to 6 months if approved for your PhD candidature. This is the full-time, tax‑exempt rate which will index annually a tuition fee offset/sponsorship, covering the cost of your