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Field
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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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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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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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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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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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, 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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tradeoffs, breeding trials across highly variable environments, and functional validation of gene effects. The candidate will (1) apply advanced analytical approaches to integrate existing datasets, (2
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for laboratory analysis. Proven record of involvement in broad research projects. Excellent data analytical skills. Demonstrated publication and presentation skills. Excellent interpersonal and communication
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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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simulations. Knowledge of behavioral and analytic methods related to representational similarity, multidimensional scaling, reinforcement learning, and fear conditioning is a plus. Experience developing and