The lab of Jian Ma within the School of Computer Science at Carnegie Mellon University is looking for Postdoctoral Researcher (at least one) to develop machine learning algorithms to address exciting problems in computational biology. The main research focus in the Ma lab is the development of algorithms to reveal fundamental connections between human genome structure and function as well as their changes in different cellular conditions, during disease development, and across mammalian species. The group also works on machine learning architectures for representation learning, methods for cohesive integration of multimodal biomedical data, and approaches for enhancing model interpretability and generalizability. Current interests in computational biology include 3D genome organization, single-cell epigenomics, spatial omics, comparative genomics, and complex molecular interactions. Recent methods from the lab have been published in journals such as Nature Biotechnology, Cell Systems, Genome Research, Nature Communications, Genome Biology, PNAS, and conferences such as ICLR, AISTATS, RECOMB, ISMB. Lab website:

The new postdoc will be expected to lead new computational method development with significant biological findings. The postdoc will also be provided with ample opportunities to integrate their new computational methods within the broad research community and foster collaborations in several NIH Consortia (e.g., 4DN, SenNet, IGVF), maximizing the potential impact of the work. The Ma lab is currently leading a UM1 Center in the NIH 4D Nucleome (4DN) Program.

- PhD degree in Computer Science, Computational Biology, Electrical Engineering, or other quantitative fields.
- A strong publication record in original method development for computational biology.
- Experience in analyzing epigenomic data and/or single-cell genomic 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.