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almost equally abundant in most organisms, highlighting the need to develop and optimize negative ion mode techniques. This project will advance the next generation of proteomics, bridging this fundamental
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during training, an effect attributed to the properties of the optimization technique. Intuitively, stochastic optimizers tend to converge to flatter minima in the complex loss landscape, which is believed
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platforms can unify production environments, enabling predictive maintenance and data-driven optimization through centralized data platform architectures. Your research will focus on addressing current
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are carried out in direct collaboration with industry to a great extent. The position is offered in relation to the research program "Power Electronic Control Reliability and System Optimization" and the PhD
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optimization of novel organic reactions, as well as substrate scope investigation including isolation and characterization of products. You must have a two-year master's degree (120 ECTS points) or a similar
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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reagents, development and optimization of novel organic reactions, as well as substrate scope investigation including isolation and characterization of products. You must have a two-year master's degree (120
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optimization of SERS substrates, Raman measurement, data analysis, and validation of results with reference methods such as high performance liquid chromatography (HPLC). You are expected to have a solid
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-objective optimization, and online decision-making approaches are relevant areas of expertise for this position. Previous experience with developing models, tools, or processes is desired. The candidate has
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of samples. To apply and further optimize data analytical workflows. A comprehensive database will be created, documenting the key chemical and physical properties of advanced bio-oils. The qualified applicant