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discovery, and computational design. Extending our existing theoretical frameworks in investigating design optimization and nonlinear parameter estimation. Contributing to the teaching and assisting with
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. Extending our existing theoretical frameworks in investigating design optimization and nonlinear parameter estimation. Contributing to the teaching and assisting with dynamics relevant courses
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, semiconductor physics, and device engineering. Are you excited to work on photo/electrochemistry? In this PhD position, you will contribute to the SUN2CN project, developing a new solar-to-X device that uses
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the Jena Experiment and collaborate closely with Prof. Dr. Alex Weigelt and Prof. Dr. Nico Eisenhauer. Together, we form a strong network of ecologists — from experimental to theoretical — working
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lacks a thorough theoretical foundation. Your duties and responsibilities include: Synthesize theoretically grounded methods for inference and spatiotemporal prediction using opportunistic samples, and
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Theoretical Biology, Epidemiology, Applied Mathematics, or a closely related field. Proven experience in mathematical modelling and quantitative analyses, with a strong motivation to apply these skills to plant
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related to staff position within a Research Infrastructure? No Offer Description Join a pioneering PhD project exploring how massive stars evolve into gravitational-wave sources. Combine stellar physics
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multiscale modelling, in close collaboration with the theoretical physicist Dr. Jos Zwanikken. Further develop the mesoscale approach to study cell polarity as a collective physical process: a conceptual
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, combining information-theoretic approaches (e.g., information bottleneck) with cross-modal modelling of time series and sensor data. The project will also explore signal-to-text generation for human-readable
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Conference on Artificial Intelligence and Statistics (AISTATS), vol. 238, pp. 550-558, 2024. H. Fokkema, T. van Erven and S. Magliacane. Sample-efficient Learning of Concepts with Theoretical Guarantees: from