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on generating new knowledge for optimizing biological conversion of carbon dioxide to acetic acid in close collaboration with an industrial end-user of the developed technology. Responsibilities and tasks Your
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focused on applying quantitative tools (e.g., statistics, machine learning, optimization, simulation) to healthcare delivery, healthcare operations and healthcare management as well as medical decision
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characterization via omics data analysis, and other computational tasks such as sequence optimization, data extraction, and DNAseq analysis. We also consider projects in data infrastructure, LLM development with
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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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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make energy districts and communities more sustainable? We are looking for a highly motivated and
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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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machine learning, computational modelling, and advanced data analytics can accelerate not only the discovery, characterization, and optimization of materials but also project assessment and communication
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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