The group of Martin Zhang within the School of Computer Science at Carnegie Mellon University is looking for a Postdoctoral Researcher to develop computational methods to address exciting problems in statistical genetics. The new postdoc will be expected to lead new computational method development with significant biological findings. The main research focus in the Zhang group is the development of computational methods to systematically map genes and cellular contexts for heritable diseases and complex traits. The group also works on deep learning methods for cohesive integration of multimodal genetics and genomics data. Current interests in statistical genetics include disease-relevant cellular contexts and genes, expression quantitative trait loci (eQTLs), single-cell genomics, and genetic architecture of diseases and complex traits. Recent methods from the lab have been published in journals such as Nature, Nature Genetics, Nature Communications, The American Journal of Human Genetics, eLife, and conferences such as NeuRIPS, ICML, AISTATS, RECOMB. Lab website:

Qualifications:

• PhD degree in Computer Science, Computational Biology, Electrical Engineering, Genetics, or other quantitative fields.
• A strong publication record in original method development for statistical genetics or computational biology.
• Experience in analyzing genetics data (such as GWAS) and/or single-cell genomics data will be a positive but is not required.

All applicants should submit a CV with a list of publications, and the names and contact information of at least three references.