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Field
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activity - Conducting catalytic tests (liquid-phase hydrogenation) - Interpreting results to understand reaction pathways and observed phenomena, and proposing practical and effective solutions to optimize
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Your Job: Design and development of a modular high throughput sample environment for chemical hydrogen storage investigations under realistic conditions Design, optimization, and testing of sample
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of life and satisfaction of its residents. https://www.enjoynordjylland.com/ Your work tasks The position is offered in relation to the EU-funded research program "STRONG UR, Strategies for optimized
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. The group will be contributing to the Physics Modeling (MC software, MC validation and Pileup modeling), the MET High-Level Trigger validation, optimization and performance studies, and to the heterogeneous
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of vegetation–climate–technology interactions to optimize energy yield in environments subject to climatic stress. Responsibilities: Monitoring PV panels: temperature, efficiency, dust accumulation. Using
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computational approaches to biological systems. Its core activity is the development of deep learning methods for protein design and optimization, with applications in biology and medicine. - activities: We
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assessment of CCUS value chains Reactor design, optimization, and sizing using phenomenological and/or CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with
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(or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs. The candidate will apply
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skills for functional genomic screen design and analysis. You will build CRISPR tools, design optimized pooled genetic screens (e.g. Perturb-seq–based approaches), and troubleshoot the experimental
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permanent staff members, plus some 15 PhD candidates and 4 post-doc researchers. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5801-GERVIG1-053/Candidater.aspx Requirements Research