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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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part of the Dynamical Systems Section. We perform research within a broad range of areas within dynamical systems including modeling, optimization, forecasting, and controlling in both deterministic 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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platforms. Experience in high-performance computing or working with large-scale simulation environments. Prior work involving model calibration, optimization under uncertainty, or scenario analysis
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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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cell factory development, data analysis and fermentation optimization. Oversee project planning, execution, and resource allocation. Provide teaching, scientific guidance and mentorship to PhD and Msc
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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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transformation, operational efficiency, and structural coherence Strong financial understanding, including cost control and gross margin optimization Excellent stakeholder management skills across academic
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translate fundamental insights in membrane technology into practical, impactful solutions. Responsibilities and qualifications Develop and optimize highly structured membranes for membrane distillation. Lead