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an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a business model. In its research approach, the UM6P promotes transdisciplinary
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to its state-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a business model. In its research
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and study environment thanks to its state-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a
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environment thanks to its state-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a business model. In its
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offers a high-quality living and study environment thanks to its state-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as
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assistants involved in related projects. Qualifications: Ph.D. in Microbiology, Environmental Biology, Soil Science, or a related field. Strong background in microbial ecology, particularly with experience in
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assistants involved in related projects. Qualifications: Ph.D. in Chemical Engineering, Biotechnology, Environmental Science, or a related field. Strong background in biomass conversion technologies (e.g
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of the formulated systems, in lab scale. Participating in workshops, national conferences and summer school activities Collaborating with world class institutions Mentoring PhD and research assistant students
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and study environment thanks to its state-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage