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.
The group is actively engaged in multi-disciplinary national collaborations with large project teams including the SCORCH consortium and the HuBMAP, as well as multiple groups from the Departments of Pathology, Immunobiology, Neurology, Genetics, Internal Medicine and the Cancer Center. The successful candidate will utilize single cell transcriptomics, spatial transcriptomics as well as other genomic, epigenomic and proteomic data from our experimental collaborators and from the public domain and develop novel techniques to characterize a variety of biological systems. The focus will be on immunology, melanoma, and lung cancers studies and single cell characterization of several brain regions relevant to persistent HIV infection and opioid use disorder. The scope of the work could extend to other systems. The successful candidates must be able to work well with groups from different disciplines and to present scientific results in a clear and effective manner.
Research projects may involve, but not limited to:
- Analysis of high throughput transcriptomics, proteomics, genomics data, such as single cell RNA sequencing data, spatial transcriptomics data in a collaborative setting.
- Data management and pipeline development for consortiums.
- Develop and implement new bioinformatics and computational biology algorithms
- Ph.D. in Computational Biology, Bioinformatics, Genetics, Computer Science, Applied Mathematics, Statistics, Physics, Engineering 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 and R programming languages is preferred.
- Interest in collaborating with biologists and physician scientists.
- Familiarity with UNIX and cluster computing is preferred.
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@example.com). In the subject line, write “your full name, postdoc application”.