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"Postdoctoral Scholars in Bioinformatics of Neurodevelopment and Neurodegeneration"

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Postdoctoral Scholars in Bioinformatics of Neurodevelopment and Neurodegeneration

Postdoctoral Researchers in the Peng Lab at UCLA. The Peng Lab at the University of California, Los Angeles, is seeking highly motivated Postdoctoral Scholars with expertise in data science and bioinformatics to drive groundbreaking discoveries in neurodevelopment and neurodegeneration of the visual system. Our team applies interdisciplinary approaches, combining multi-omics, genetics, molecular biology, evolutionary biology, viral tools, advanced bioinformatics, and statistical modeling to decode the complex molecular mechanisms that shape human vision. By leveraging high-dimensional data and cutting-edge computational analyses, we aim to uncover fundamental insights into visual system development, function, and disease.

Why Join Us? As a postdoctoral fellow, you will have the opportunity to lead innovative research, collaborate with top scientists, and develop novel computational approaches to analyze complex biological datasets. We are committed to fostering the academic and professional growth of our fellows in a dynamic and supportive research environment. Fellows will have access to state-of-the-art computational and experimental tools, mentorship from experts across disciplines, and opportunities to present their work at prestigious conferences and in high-impact journals.

  • Lead projects on developing novel analytical methods for studying the development and degeneration of the visual system
  • Acquire, process, integrate, and standardize large-scale multi-omics datasets and build databases
  • Perform integrative and exploratory analyses of multi-omics datasets and apply machine learning methods to uncover underlying biological principles

Selection Criteria:

  • Ph.D. in data science, computational biology, systems biology, bioinformatics, neuroscience, or other related fields
  • Strong experience in data analysis and handling omics datasets - genomics, transcriptomics, and proteomics
  • Proficiency in R, Python, and other programming languages
  • Expertise in Linux, Git, Docker, and other high-performance computing environments
  • Excellent communication and writing skills, with the ability to collaborate effectively in a team

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