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Field
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
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 The successful
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, and contact information for 3 references. Required Qualifications - PhD in Mechanical Engineering, Materials Science and Engineering, Polymer Science and Engineering, Electrical Engineering or a related
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funded by UKRI and is fixed-term to 31 December 2026. This is an on-site position only. The project aims to develop a computational model for biodegradable polymers degrading in water under mechanical
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, Polymers and Composites, and Sustainable Materials. With some 100 researchers and PhD students and several national and international partners, MSN is emerging as a strong actor in the Moroccan materials
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13 Jan 2026 Job Information Organisation/Company University of Ostrava Department Faculty of Science Research Field Biological sciences Researcher Profile Recognised Researcher (R2) Positions PhD
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Biotechnology research at Aalto University. The lab will develop next-generation methods to evaluate, understand, and engineer biodegradation of polymers such as plastics, microplastics, and textile-derived
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, including degradable polymers, block copolymers, and responsive materials. Develop protein/gene delivery formulations, including Cas9 RNPs, therapeutic enzymes, or antibody fragments. Engineer stimuli
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appointment in Pullman, WA, with a specialty in the in the areas of nanomedicine, targeted drug delivery, and polymer/dendrimer chemistry. The Sharma lab is developing rationally designed, smart, clinically
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, and analyze new lipids or polymers for nucleic acid delivery • Formulate and characterize LNPs for mRNA, siRNA, and small-molecule applications • Perform in vitro studies, including mammalian cell
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methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing