Research Associate in machine learning & genomics for human brains

University of Wisconsin – Madison
Waisman Center and Department of Biostatistics and Medical Informatics
United StatesWisconsinMadison


NIH-funded Postdoctoral Research Associate positions are available in the laboratory of Dr. Daifeng Wang ( in the Waisman Center and the Department of Biostatistics and Medical Informatics at the University of Wisconsin – Madison. This position aims to develop and apply machine learning approaches and bioinformatics tools to analyze emerging single-cell multi-modal data for understanding functional genomics in the human brain and brain diseases and achieving precision medicine. The selected candidate(s) will work in an interdisciplinary environment and have a chance to collaborate with PIs from Waisman Center, UW-Madison, and other top institutes. She/he will also be able to contribute to several NIH scientific consortia (e.g., BRAIN Initiative, PsychAD, PsychENCODE) and participate in lab development, supervising students, and grant applications.

Daifeng Wang Lab focuses on developing interpretable machine learning approaches and bioinformatics tools to open the “black-box” in complex brains and brain disorders and understand underlying functional genomics and gene regulatory mechanisms. Recent work has been published in high-profile journals such as Science, Nature, Nature Computational Science, Genome Medicine, Cell Systems, PLoS Computational Biology, Bioinformatics. Please find details at .

Madison, Wisconsin is the #1 Best City to Live in the USA ( ).


The applicant(s) should have a Ph.D. or equivalent degree in bioinformatics, computer science, data science, engineering, biology, physics, or related areas with basic programming skills (e.g., R, Python). Prior experience in next-generation sequencing data, bioinformatics software development, and machine learning is preferred but not required.

Start date

As soon as possible

How to Apply

Applicants are requested to send a CV and a list of 3 references to .


Dr. Daifeng Wang