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Field
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remaining functional under harsh geothermal conditions. The candidate is expected to work closely with D-TECH and may undertake a secondment period to test and apply the developed methods on industrial-scale
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knowledge of numerical methods - knowledge of free-surface flows, granular flows - proven experience in numerical simulation (finite elements, finite volumes, CFD, LES, etc.) - proficiency in basic scientific
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accuracy requires high spatial and temporal resolution, which is time-prohibitive and therefore impractical for large parts. This project therefore aims to develop numerical methods that enable the efficient
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challenges facing modern societies. Specifically, the tasks are: Identify state‑of‑the‑art machine‑learning (ML) methods that can be applied to geochemical systems in geological contexts Assess these methods
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to the proposed control methods in respect of heat transfer and drag. *Keywords : flow control, heat transfer, wall-bounded flow, thermal boundary layer, numerical simulations, reduced order model, machine learning
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Earthquake Engineering and examines the dynamic and liquefaction behavior of Icelandic basalt sand, using laboratory test methods and advanced numerical techniques. The project is funded for three years by
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. Experience with isotopic box modeling, numerical simulations, and statistical analysis. Demonstration of effective communication of scientific and technical results (e.g., peer-reviewed publications
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Are you fascinated by electromagnetic modeling and numerical problem solving? Do you want to contribute to the development of state-of-the-art metrology for integrated-circuit production
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
. Such structures can be used to construct artificial cell mimics and new materials. A scaffold-free DNA tile assembly is a programmable method for the formation of two- and three-dimensional DNA structures which
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associated numerical methods and AI, will be used with High Performance Computing (HPC) to improve understanding of key flow physics and inform future HPT design. Skills and Experience Required: Applicants