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landscapes. Collaborate with multidisciplinary teams to integrate remote sensing data with ground-based observations, physical algorithms, and machine learning models. Participate in field data collection and
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-based observations, physical algorithms, and machine learning models. Participate in field data collection and validation to support model accuracy. Publish research findings in peer-reviewed journals and
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recently completed (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
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oriented institution of higher learning, that is committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
Computational Chemistry, Materials Science, or a related field. Strong background in computational chemistry techniques, including molecular dynamics, quantum mechanical simulations, and machine learning
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. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large
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dynamics, quantum mechanical simulations, and machine learning. Proficiency in programming languages and computational software’s. Strong motivation and passion for research in the field of sustainable
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-driven modeling, simulation and optimization with strong and permanent interactions with experiments. Integrate artificial intelligence (i.e. machine, deep and reinforcement learning…) to optimize
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research, oncology microbiomes, or environmental resistome surveillance. Familiarity with spatial metagenomics, single-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning