Xing Lab Post Doctoral Associate

Itemergesasanexcitingnewfieldbothinquantitativebiologyandcomputational biologyonstudying how eukaryotic cells make cell fate decisions and convert between different cell types by integrating big data analyses and mechanistic studies 1 . My lab has been focusing on putting single cell high throughput (e.g., sequencing and imaging) data analyses within the framework of mechanistic modeling 2-8 .

The Xing Lab Has An Immediate Opening For a Highly Motivated Researcher At The Postdoc Level. The Ideal Candidate Will Have a PhD In Biological Physics, Quantitative Biology, Bioengineering, Mathematical Biology, Or a Related Field, With Demonstrated Expertise In Using Dynamical Systems Theories, And/or Machine Learning/AI Approaches For Studying Biological Processes Through Single Cell Genomics Data Analyses, And/or Mechanistic Studies Of Cellular Processes. The Researcher Will Collaborate With Other Lab Members And External Collaborators At Harvard, UCLA, UPitt, Etc. Competitive Candidates For The Postdoc Are Expected To

• Possess experience in single-cell omics data analysis;
• Bring additional expertise in AI/ML or dynamical systems theory–based modeling, or be willing to collaborate closely with lab members who have these backgrounds;
• Demonstrate strong motivation and enthusiasm for learning new skills;
• Show a record of productivity, including first-author publications.
  
  

Preference will be given to applicant expected to receive a PhD degree within half a year or have received within 1-2 years.

After applying, please send CV and a research plan to xing1@pitt.edu . After initial screening, I may ask three reference letters arranged to be sent to me directly.

• Xing, J. Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology. Physical Biology 19 , 061001 (2022).
• Qiu, X. et al. Mapping Transcriptomic Vector Fields of Single Cells. Cell 185 , 690-711 (2022).
• Hu, S. et al. Epithelial-mesenchymal transition couples with cell cycle arrest at various stages. bioRxiv , 2025.02.24.639880 (2025).
• Zachary, R.H. et al. Dynamical modeling reveals RNA decay mediates the effect of matrix stiffness on aged muscle stem cell fate. bioRxiv , 2023.02.24.529950 (2023).
• Chen, Y. et al. GraphVelo allows for accurate inference of multimodal velocities and molecular mechanisms for single cells. Nat Commun 16 , 7831 (2025).
• Wang, W. et al. Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data. Science Advances 6 , eaba9319 (2020).
• Wang, W., Ni, K., Poe, D. & Xing, J. Transiently Increased Coordination in Gene Regulation During Cell Phenotypic Transitions. PRX Life 2 , 043009 (2024).
• Wang, W., Poe, D., Yang, Y., Hyatt, T. & Xing, J. Epithelial-to-mesenchymal transition proceeds through directional destabilization of multidimensional attractor. eLife 11 , e74866 (2022).
  
  

Med-Computational and Systems Biology

Assignment Category

Full-time regular

Campus

Pittsburgh

Child Protection Clearances

Not Applicable

Required Attachments

Cover Letter, Curriculum Vitae