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energy-innovation technologies. Applying catalysis and reaction-engineering approaches, the role targets low-carbon fuel pathways—such as hydrogen, ammonia, synthetic and electro-fuels, sustainable
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artificial intelligence (AI) methods that propose, prioritize, and interpret experiments, accelerating the discovery and optimization of catalytic materials for energy and sustainability applications
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About the Opportunity Summary: Research involves developing and implementing material models to predict microstructure, phase change and residual stress in processes in high energy processes in
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. The research focus is on developing and applying first-principles-based and data-driven computational methods to understand multiscale processes and accelerate chemical discoveries for renewable energy
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, dissect peptide-immune cell interactions, and examine how the peptide shapes the gut microbiome. The anticipated start of this position is September 2026, with yearly renewals based upon funding and
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engage in collaborative work with cell and developmental biologists. Expertise in agent-based models, continuum PDE descriptions, dynamical systems, and/or ML-based surrogate model discovery are strongly
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biochemistry, genetics, microbiology, and cell biological approaches. For more information check the Saavedra lab website: https://www.saavedralab.com The successful candidate for this role will join a
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, Western blot) Strong in vitro skills including immune cell and co-culture assays, cell-based immunological assays, inflammatory models. Strong analytical skills and attention to detail. Excellent
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students. Other duties as assigned. Qualifications: Applicants should have a PhD degree in Neuroscience, Immunology, Cell and Molecular Biology, Biology or a related field. Strong candidates will have a
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About the Opportunity Job Summary The Copos Group works on computational and mathematical theoretical models with direct applications to several open problems in cell biology. We are specifically