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Laboratory. You will be responsible for: • Advancing numerical modelling methodologies for 3D woven composites • Designing and conducting high‑rate and impact experiments on 3D woven composite architectures
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lung fibrosis. The ideal candidate will independently perform studies utilizing established in vitro, ex vivo and in vivo preclinical models and will have the opportunity to develop and refine novel
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the Hobbs Laboratory focuses on understanding how epithelial cells sense and respond to cellular, environmental, and inflammatory stress. Using skin keratinocytes as a primary model system, the laboratory
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technologies, digital soil mapping/pedometrics, proximal/remote sensing, and geospatial modeling. The ideal candidate will work and collaborate closely within a research team at Texas A&M AgriLife and USDA-ARS
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biological approaches, in vitro cell culture systems, and novel mouse models. Optimal candidates will have experience with immunometabolism and use of these techniques and models. The overall goal is to
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programming/scripting (Bash,Python) Preferred Qualifications The candidate should have demonstrated experience in molecular modelling, particularly in the areas of biophysics or material design (all atom
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peripheral blood stem cell transplantation and tumor models. Studies may also include use of human cells and humanized NSG mouse models. Ongoing research includes novel approaches in activating anti-tumor
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of electrochemistry and artificial intelligence. Ideal candidates will have experience in machine learning, large language models, AI-agent development and computational workflows, with particular interest in building
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Challenge: Predict long-term cardiac growth and remodeling in cardiovascular disease. Change: Develop multi-scale mechanobiological models for virtual human twins. Impact: Advance patient-specific
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, which remains a major global health challenge and an important cause of liver related morbidity and mortality. Our laboratory has a strong history of developing innovative human models of viral infection