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Field
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scientific breakthroughs. The successful candidate will lead research on ERC PoC project PepVerse within Prof. Knowles' research group at the Yusuf Hamied Department of Chemistry at the University of Cambridge
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, architecture, and/or industrial design. You also possess: Strong analytical skills and innovative attitude Previous experience with finite element simulations and/or rapid prototyping Good programming and image
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to lead impactful research at the interface of aging biology, neurodegeneration, and spatial omics. The successful candidate will contribute to high-profile projects investigating the cellular and molecular
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physics (e.g., Turing patterns). This will involve: (i) developing new analytical/theoretical tools for the study of reaction-diffusion systems, (ii) performing large scale, machine-learning-assisted
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University of North Carolina at Greensboro | Greensboro, Indiana | United States | about 2 months ago
Posting Details Position Information Position Number 999949 Functional Title Post-Doctoral Fellow Position Type Post-docs Position Eclass EP - EHRA 12 mo leave earning University Information Located
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of this position within the team is the experimental work on decontamination of porous materials, although it is also expected that the successful candidate will contribute strongly to the analytical and numerical
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, evaluate material performance, and assess food packaging applications. Operate and optimize polymer processing techniques, including extrusion, to develop sustainable material prototypes. Apply analytical
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, engineering, computer science, and machine learning. The postdoctoral fellow will assume scientific leadership for one observatory site and will: Lead site commissioning, including performance verification and
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and detail-oriented Postdoctoral Scholar to lead experimental investigations into how aging alters the tumor microenvironment (TME) and efficacies of immunotherapies in breast cancer. The research will
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lead research projects to investigate how bioactive lipids and other related bioactive compounds influence chronic diseases using advanced analytical techniques and statistical methods under Dr. Liang’s