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graphene-based field effect transistor sensors with biological receptors for infection biomarkers, and optimize this technology for diagnosing infections in the wound settings. As a postdoctoral researcher
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dynamics, such as hidden Markov models or statistical jump models, affect the optimal decision-making process for an investor. Specifically, we aim to develop new methods for regime models, including
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include: Benchmark study: Compare and evaluate methods and models for digital twin simulation in autonomous shipping, and integrate them into a cohesive model. Energy optimization: Develop a dynamic energy
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methods and models for digital twin simulation in autonomous shipping, and integrate them into a cohesive model. Energy optimization: Develop a dynamic energy optimization model for hybrid and electrified
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consists of 18 research groups covering a wide range of mathematical disciplines – from pure and applied mathematics to numerical analysis and optimization, as well as mathematical statistics and machine
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maximal signal-to-noise and detection of picomolar levels of protein in the blood. The laboratory’s part of the project is to test and optimize this new strategy and subsequently use it to evaluate
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of the active material through an intrinsic buffer effect. The overall aim is to design new materials and optimize fundamental battery performance, as well as to achieve increased mechanistic understanding
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the optimization of cultivation processes and freeze-drying formulations for health-promoting bacterial strains, as well as the evaluation of application methods and concentrations for postharvest treatments
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to numerical analysis and optimization, as well as mathematical statistics and machine learning. The centre offers a lively academic environment where colleagues from many parts of the world come together
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crucial role in controlling risk. The project aims to investigate how abrupt changes in dynamics, such as hidden Markov models or statistical jump models, affect the optimal decision-making process for