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composites, and sustainable materials. With over 70 researchers and PhD students, and strong national and international collaborations, MSN is a growing force in materials research. Job Description
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sustainable and optimized processes for vanadium extraction and purification, with the goal of enabling large-scale redox flow battery deployment for energy storage. Scope of Work The successful candidate will
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computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials. The ideal candidate should have a strong background in artificial intelligence and
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process optimization. Main responsibilities: Conduct literature review on phosphate ore and waste processing and valorization; Operate and maintain mineral processing and analytical instruments; Design and
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biological approaches, with the objective of identifying optimal pathways for resource recovery. The project will also focus on the combined treatment of phosphogypsum and brines, studying the synergistic and
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to develop predictive models for polymer-based materials. This project aims to leverage computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials
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candidate will have 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
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precise, customized fertilizer recommendations. Selection criteria (short) Required PhD (awarded or defended before start) in Computer Science, Remote-Sensing/Geoinformatics, Agricultural Data Science, or
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: Immediate Required Level: PhD in Cell Biology, Biotechnology, Biochemistry, or a related field Main Responsibilities: We are seeking a motivated postdoctoral researcher to join our research team as part of
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
models for polymer-based materials. This project aims to leverage computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials. Key duties