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whole-body cancer detection. We are interested in both technical development and clinical translation pipelines, leveraging resources at the Lucas Center for Imaging, synergies across the clinical MRI
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substitution in the EGFRvIII peptide significantly increases survival in an animal model of glioblastoma by enhancing proteasomal processing. We also developed robust methods to detect a new class of non
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(link is external) ; https://www.science.org/doi/10.1126/sciadv.adm8680 (link is external) ). The data will be used to model exposure levels and potential impacts from any health-damaging pollutants co
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reveal the driving forces of macrophage polarization and to identify early-detection cancer biomarkers. It builds on our previous research revealing functional markers of human macrophages (Matusiak et al
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on hotspot detection. This modeling work is well supported by large-scale primary datasets, including survey-based, parasitological, serologic, and genomic data. Relevant methodologies include mechanistic
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the robustness to address national security challenges in cybersecurity. In particular, the postdoc will focus on applying reinforcement learning to discover vulnerabilities and failure modes in software systems
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advanced technologies of patient-based iPS cells, CRISPR gene editing, optogenetics, and functional retinal imaging to discover the mechanism of disease and develop new treatments for these blinding diseases