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that come in touch with human skin can serve as vehicles for transport of diseases and their spread throughout human communities. This infection process can be mitigated by surfaces on which microbes cannot
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perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join a highly collaborative
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. The Digital and Computational Pathology Laboratory in PCS is seeking a talented and motivated postdoctoral fellow to develop cutting-edge methodologies in computer vision and AI to power whole slide image
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. fluorescence imaging, molecular biology, cell culture, immunohistochemical assays, circuit manipulations, mouse surgery or behavioral assays) and electrophysiological recording (in vivo extracellular recordings
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analogous processes in more complex human cellular systems. The research aims to establish mechanistic understanding of molecular networks that maintain homeostasis under stress conditions. Through rigorous
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, develop, and optimize new methods and techniques to address critical project or functional area needs. Participants will improve existing or develop new laboratory methods and processes, read and adapt
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strategies that modulate the crosstalk between tumor and immune cells, and develop new image-based screening technologies to identify targets that mediate clinically-relevant cell-cell interactions
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hands-on experience with advanced techniques, including patch clamp, optogenetics, fluorescence imaging, auditory brainstem response (ABR), stereotaxic surgery, RNA-seq, and computational modeling
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applicant will have an opportunity to work closely with a diverse scientific team that includes microbiologists, immunologists, cell biologists and bioinformaticians. Who You Are: Recent PhD in the field
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years of research experience in biology or a related discipline. Publication record demonstrating computational skills in image processing or genomic data analysis. Proficiency in rodent neurosurgeries