Important Info
SUBJECT LINE: Applicant Name, Fang lab Postdoc Application
to Dr. Rongxin Fang r3fang@stanford.edu
The Fang Lab of Neurogenomics (fanglabstanford.org) at the Wu Tsai Neurosciences Institute, Stanford University, is seeking postdoctoral fellows to join our team. We are looking for postdoc candidates to develop and apply cutting-edge technologies in spatial transcriptomics, single-cell sequencing, machine learning, and functional genomics to investigate the molecular and cellular mechanisms of intercellular communication in the healthy brain and in tumor microenvironment (TME).
The major focus of our lab is to advance technologies including single-cell genomics, transcriptome imaging, optical electrophysiology, and machine learning to study how the genome builds a brain across spatial and temporal scales. Key questions we aim to address include:
1. At single cell level, how does the same genome give rise to thousands of different cellular phenotypes in the brain?
2. At the tissue level, how do gene networks orchestrate intercellular communication between different brain cell types?
3. In living cells, how do genomic variations influence cellular communication, behavior and dynamics?
The successful applicant will lead a project focused on developing single-cell sequencing, spatial transcriptomics, and machine learning algorithms to to understand, at the tissue and organ level, how specific cellular communications—from synaptic connectivity to neural-immune interactions—are synchronized by gene networks, how these processes malfunction in disease, and ultimately apply this knowledge to engineer cell communication for therapeutic purposes.
- Doctoral degree (PhD or equivalent) in Genomics, Bioengineering, Biology, Biochemistry, or a related field.
- Experience in developing single-cell sequencing technologies is highly desirable.
- Prior experience with optical imaging, spatial genomics, or super-resolution microscopy is a strong plus.
- Creative, highly motivated individuals with strong problem-solving skills, a proven record of scholarly productivity, and the ability to work both independently and collaboratively in a multidisciplinary environment (involving clinicians, computer scientists, and statisticians).
- A strong background in Bioinformatics, computational analysis is preferable.
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Excellent communication skills and fluency in spoken and written English.
- Cover letter that describes your research interests and background
- Current CV with publication list
- Contact information for three references