Two postdoc positions in single cell transcriptomics and spatial trancriptomics/proteomics
51 Prospect Street
New Haven, CT 06511
Two postdoctoral positions in computational single-cell RNA sequencing and spatial transcriptomics & proteomics are available in the laboratory of Dr. Yuval Kluger at Yale University School of Medicine. The Kluger Lab is affiliated with the Applied Mathematics program in the Department of Mathematics, Computational Biology & Bioinformatics program, as well as the Yale Center for Biomedical Data Science and the Yale Cancer Center.
The group is focused on methodological development of novel computational methods including deep learning, graph theory, and spectral approaches to analyze high-throughput and high-dimensional biomedical data. Most of our current applications concentrate on analysis of data generated in single cell RNA sequencing and spatial transcriptomics/proteomics studies which provide unprecedented opportunities to conduct detailed analyses of cell subpopulations. Fulfilling the promise of these studies and biomarker discovery requires robust computational approaches to support detection of rare phenotypes and unanticipated cellular responses. Current approaches for denoising, calibration, clustering and visualizing of such data types suffer from challenges such as erroneous imputation of non-expressed genes, removal of multivariate batch effects, detection of local differences between cell distributions, and inefficiencies of clustering and dimensional reduction methods of very large datasets. We have developed novel and efficient spectral and neural network prototypes suitable for addressing these issues in high throughput data contexts and further develop and adapt these methods to data generated by our collaborators.
Research projects may involve, but not limited to:
- Develop and/or implement new algorithms for addressing challenging problems in the fields of scRNA-seq and spatial transcriptomics
- Analysis of high throughput transcriptomics, proteomics, genomics data, such as single cell RNA sequencing data, spatial transcriptomics data in a collaborative setting.
- Ph.D. in Computational Biology, Bioinformatics, Computer Science, Applied Mathematics, Statistics, Physics, Engineering, Genetics or other related fields.
- Proficiency with the analysis of next generation sequencing data.
- Ability to develop, implement and benchmark computational methods.
- Solid programming skills.
- Experience with Python or R programming languages is preferred.
How to Apply
Qualified candidates who are interested in applying should e-mail an application package, including: statement of interest, CV, and contact information for references. Please send your application package to Dr. Yuval Kluger ([email protected]). In the subject line, write “your full name, postdoc application”.