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models for each study site, informed by sensor networks and image-based observations. Conduct cross-disciplinary geospatial analyses linking modeled flooding patterns with soil pathogen and participant
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processing of social information in patients with psychiatric conditions remain largely unclear. We use a suite of cutting-edge techniques, including in vivo multi-photon imaging, fiber photometry, and custom
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disease with a focus on Alzheimer’s Disease. Computational models will be developed that utilize data obtained from a wide range of experiments, from basic biochemical methods to advanced imaging techniques
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healing, and nuclear mechanosensing. The successful candidate will have established experience in the following areas: (a) imaging techniques such as fluorescence, confocal, and multi-photon microscopy, (b
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coding skills in UNIX and Python. (R experience is welcome but secondary.) Previous experience in NGS data analysis and genomics pipelines. Prior first-author publications. Strong problem-solving skills
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with a group of highly motivated scientists to employ interdisciplinary approaches such as retinal cell biology, functional genomics, imaging, and biochemistry. The Chen Lab has a well-recognized
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interpreting findings. Writing journal articles and project progress reports. Assisting with grant management, including supervising project students. Organizing data and code repositories for promoting open
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their degree in the near future) in Cancer Biology or a related field. Proficiency in experimental techniques such as cell/organoid culture, library construction, imaging and handling animal models. Experience
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vulnerability or survival during neurodegenerative conditions in vivo. Responsibilities of the postdoc will include, but are not limited to: in vivo imaging of biosensors to read out diversity and dynamics
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demonstrated scholarly production (e.g., list of publications, presentations, public datasets, or code) 3. A representative example of your scholarly work/s 4. Names, addresses, emails, and telephone