Postdoctoral Associate

Job Description

Dr. Shenglin Mei lab at the Fralin Biomedical Research Institute (FBRI) Cancer Research Center- DC is seeking highly motivated Computational Biology postdoctoral fellow to join our team.

The Mei Laboratory studies the remodeling and regulatory mechanisms of the tumor microenvironment during tumor progression and metastasis. The lab combines single-cell technologies, genomic datasets, machine learning, and experimental methods to investigate how the tumor microenvironment and gene regulatory factors control tumor metastasis cascade. By advancing our understanding of malignant cell heterogeneity and tumor microenvironment remodeling, we aim to drive the development of novel therapeutic approaches for patients with metastatic cancer. The current focuses in lab include the following directions: 1) Developing computational methods for integrating multi-modal data, such as scRNA-seq, scATAC-seq, spatial transcriptomics, ChIP-seq, and CRISPR screening. 2) Investigating context-dependent remodeling of the tumor microenvironment. 3) Identifying novel regulators within the tumor microenvironment. 4) Exploring tumor organ specific metastasis with multi-omics data integration.

The successful candidates will collaborate with researchers at Virginia Tech as well as have the opportunity to collaborate with colleagues at the Children’s National Hospital, including those co-located on their research and innovation campus.

Required Qualifications

- PhD and/or MD in Computational Biology, Bioinformatics, Genomics, Biology, Data Science, Computer science or other related fields. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
- Experience in high-throughput sequencing data analysis.
- Track record of first/co-first-author original research papers.
- Strong programming skills in Python or R, and Linux Shell.
- Creative, independent, and highly motivated, with good communication skills

Preferred Qualifications

- Experience in developing algorithms for analysis of biological data.
- Experience with single cell and spatial transcriptome data analysis.
- Experience in supervised and unsupervised machine learning, or deep learning models

Appointment Type

Restricted

Salary Information

Commensurate with experience

Review Date

11/4/2024

Additional Information

The successful candidate will be required to have a criminal conviction check.

About Virginia Tech

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

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If you are an individual with a disability and desire an accommodation, please contact Brittany Shelton at sheltb@vtc.vt.edu during regular business hours at least 10 business days prior to the event.