Welcome to the Lab Page of Rumi Chunara, Assistant Professor at New York University.

The overarching goal of our research is to develop the principles needed to incorporate unstructured data into a better understanding of our health. We primarily develop computational and statistical methods across data mining, natural language processing, spatio-temporal analyses and machine learning, to study population-level public health.

**Postdoctoral positions available – see description below**

*Chunaralab undergrad researcher William Herrera accepted to the prestigious NIH Summer Internship Program in Biomedical Research.

*Nabeel Rehman will present his work on Using Propensity Score Matching to Understand the Relationship Between Online Health Information Sources and Vaccination Sentiment at the AAAI Spring Symposium at Stanford University in March 2016.

*Prof. Chunara was an invited speaker at a panel on Web-Based Public Health Informatics at IEEE BHI ’16 in February 2016.

*Bisakha Ray presented her work on Integrating Genomic Data in a Community-based Multi-modal Viral Transmission Model for Network Inference at the NIPS Workshop on ML for Healthcare in Montreal, December 2015.


Watch the below video to learn about our research mission:


Post-doctoral opportunity in developing novel computational approaches for disease surveillance. The Chunara Laboratory in Computer Science & Engineering, and the College of Global of Public Health at New York University is seeking highly motivated researchers to develop and study crowdsourced and point-of-care data for understanding infectious and chronic disease in populations worldwide.

Ideal postdoctoral candidates will have a Ph.D. with a strong background in bioinformatics, biostatistics, computer science or related field. Expertise in statistical machine learning and/or data mining are required. Preferred requirements for this position include experience designing software applications and/or storing, retrieving, and analyze large datasets. Experience with R, Python, SQL, JavaScript is preferred. Experience in hacking with cloud technologies (e.g., AWS, Hadoop) is a big plus. You must demonstrate an interest or experience in working with biological data such as genomic sequence, syndromic surveillance or physiological data.

This is an exciting research area and New York City provides great opportunities for networking and support of innovative work. Our group is engaged in many high-profile studies in collaboration with startups and other groups. The selected post-doc will be supported and encouraged to generate high impact publications, gain experience in supervising students and in grant writing if interested. All applicants should send an updated CV to Rumi Chunara (rumi.chunara@nyu.edu)