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) for engineering systems. Our research covers surrogate modeling, reliability analysis, sensitivity analysis, optimization under uncertainty, and Bayesian calibration. We are known for developing the UQLab software
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experience in developing software for scientific applications, data analysis, or real-time systems is desirable. Experience with parallel computing and optimization techniques for handling large datasets
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). An optimal background for the project would be Electrical Engineering bachelor's (sensing, signal processing) with a more Computer Science-oriented master's (machine learning, time series processing). This is
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-relevant research challenges such as controlling high precision production machines, optimizing machine tools, or conceiving sustainable manufacturing processes. This position is envisaged to be part of
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the Multiphase Fluid Dyamics group (Prof. Supponen) has a focus on modelling and high-speed imaging to optimize bubble generation and control, and the resulting particle dynamics and interaction with cells using
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. The optimal exploitation of digital tools in system development processes facilitates an effective and efficient process. To effectively capitalise on the existing knowledge base, digital tools, e.g., large
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Our research group focuses on the development of AI algorithms for industrial applications. The main scope of our activities is the optimization and automation of workflows and production systems
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) for engineering systems. Our research covers surrogate modeling, reliability analysis, sensitivity analysis, optimization under uncertainty, and Bayesian calibration. We are known for developing the UQLab software
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(FTEs) and Functional Service Providers (FSPs) in the assigned countries. This position works with the team to optimize trial delivery and operational performance while ensuring compliance with Good
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/jiec.13205 Komkova A., Habert G. 2023. Optimal supply chain networks for waste materials used in alkali activated concrete fostering circular economy. Resources, Conservation & Recycling. DOI:10.1016