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of Systems and Synthetic Biology, Wageningen University(The Netherlands). Informal enquiries can be made to Pablo Carbonell pablo.carbonell@csic.es . Where to apply Website https://lifehub.csic.es/synbio
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Application deadline: 30/06/2026 Research theme: Applied Mathematics, Continuum Mechanics, Nonlinear PDEs How to apply: https://uom.link/pgr-apply-2425 UK only due to funding restrictions. The
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for the monitoring and prognostics of complex systems, characterized by high heterogeneity, nonlinear dynamics, and operational uncertainty. The main objective is to enhance the ability to promptly detect anomalies
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on inverse multiple-scattering algorithms. Implement and evaluate both linear approximation models and nonlinear high-order scattering approaches for accurate imaging of thick and strongly scattering
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processes, regularity theory of nonlinear degenerate and singular elliptic and parabolic PDEs, free boundary problems, optimal control of free boundary systems with distributed parameters. Current areas
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, 100% funded PhD student position to fill starting around June 2026. Research is to be in the field of computational methods in nonlinear and large scale optimization / inverse problems or in novel
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tracking. Specifically, advance photocurrent detected broad-band ultrafast micro-spectroscopy, towards nonlinear current/fluorescence detected multidimensional micro-spectroscopy. Contribute to publications
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Demonstrated prior experience simulating a complex system and comparing to experiment Expertise in solving highly nonlinear and coupled equations. Experience with Python or C++ and both Git and UNIX Excellent
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knowledge in mechanical vibrations and nonlinear dynamics, demonstrated through scientific publications and successful completion of 2nd and 3rd cycle (Master’s and PhD level) curricular units (proven
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PostDoc/Senior Scientist - Process and Plant Design in the Field of Liquid Organic Hydrogen Carriers
languages (e.g., Python, Julia, Matlab) Strong interest in process modeling and simulation, including novel methods and approaches such as neural networks and nonlinear optimization Ability to analyze complex