Openings

Postdoctoral researcher

The Zhang Lab is seeking one postdoctoral researcher. The researcher will work with Dr. Martin Zhang on problems in statistical genetics and machine learning, involving algorithm design, software implementation, and studying problems in statistical and/or evolutionary genetics. The researcher will have the flexibility to choose their projects or propose new projects, broadly in line with the lab’s research directions. One research focus would be to use SNP-to-gene links (such as eQTLs or enhancer-gene links from single-cell multiome) to identify GWAS genes. Dr. Zhang will provide hands-on guidance in conducting research and writing papers, as well as ample opportunities for collaboration (within and outside CMU) and presenting research works. Dr. Zhang will support the researcher’s application for a Lane Fellow, a prestigious postdoctoral fellowship program in CMU computational biology.

Qualifications:

  • Successful research experience as demonstrated by publications in peer-reviewed journals and conferences.
  • Strong skills in algorithm design, mathematical modeling, and programming (e.g., Python or R).
  • (Preferred but not required) Experience in analyzing genetics and genomics data, such as GWAS and scRNA-seq

Apply: please contact Dr. Martin Zhang via email with the title “Applying for a postdoctoral researcher position in Martin Zhang’s Lab” and include your CV, a short introduction, and your research interests.

PhD students

The Zhang Lab is seeking 1-2 highly-motivated PhD students. The students will work with Dr. Martin Zhang on problems in statistical genetics and machine learning, involving algorithm design (occasionally proving theorems), software implementation, and studying problems in statistical and/or evolutionary genetics. The students will have the flexibility to choose their projects or propose new projects, broadly in line with the lab’s research directions. Dr. Zhang will provide hands-on guidance in conducting research and writing papers, as well as ample opportunities for collaboration (within and outside CMU) and presenting research works.

Qualifications:

  • Admitted to a CMU PhD program.
  • Strong skills in algorithm design, mathematical modeling, and programming (e.g., Python or R).
  • (Preferred but not required) Experience in analyzing genetics and genomics data, such as GWAS and scRNA-seq

Apply: please contact Dr. Martin Zhang via email with the title “Applying for a PhD student position in Martin Zhang’s Lab” and include your CV, a short introduction, and your research interests. This position is only available to admitted PhD students at CMU. It usually starts with a rotation in the lab and may later evolve into a formal alignment.

Research interns

The Zhang lab welcomes graduate and undergraduate research interns from CMU. The students will work with Dr. Martin Zhang on problems in statistical genetics and machine learning. The students will have the flexibility to choose their projects or propose new projects, broadly in line with the lab’s research directions. The projects are expected to have a smaller scale and a short cycle (e.g., 6-9 months for a conference or a short journal submission). Dr. Zhang will provide hands-on guidance in conducting research and writing papers, as well as ample opportunities for collaboration (within and outside CMU) and presenting research works.

Qualifications:

  • Strong skills in algorithm design, mathematical modeling, and programming (e.g., Python or R).
  • (Preferred but not required) Experience in analyzing genetics and genomics data, such as GWAS and scRNA-seq

Apply: please contact Dr. Martin Zhang via email with the title “Applying for a research intern position in Martin Zhang’s Lab” and include your CV, a short introduction, and your research interests. This position is usually unfunded with exceptions. CMU Master’s students can register for research credits. CMU Master’s students, when not registering for research credits, may be compensated with a standard hourly pay; the paid position usually requires the student to be highly experienced.