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Collaborate with Us!

We are committed to Open Science and would love to work with collaborators to advance progress. The Huang lab has clear operating procedures with README for Collaborators/Volunteers. We focus on computational works; the website linked to this Google doc listed under Science has a few courses and/or the training suggested by BRN that you could go through first. After understanding these thoroughly, your level in genomics/biomedical data science should be get closer to that of early-year Ph.D. students and you will be capable of contributing meaningfully. At that point (or if you already feel you already have codes of such level), please send Dr. Kuan-lin Huang your GitHub with code samples and a paragraph describing your interests in our work. Volunteers can leverage the large-scale datasets that we have curated or our software to tackle their questions of interest. We also welcome inquiries of collaboration from and outside of ISMMS. Please see our collaboration record on the Publication page. 

Open position: Instructor, Postdoctoral Scholar, or Scientist 

We are recruiting instructors, postdoctoral scholars, or scientists with expertise in Statistical Genomics, Multi-Omics, and Machine Learning. We welcome scientists at all levels, and from all geographical or institutional backgrounds, to volunteer or apply for open positions. Responsibilities include:
1. Lead at least 2 high-impact projects that will translate to substantial scientific and clinical advancement.
2. Become an expert in at least 1 high-dimensional data type, 1 computational/data science approach, and 1 biological/medical domain. Utilize your expertise to guide and collaborate with colleagues in and out of the lab for co-authorship opportunities.
3. Present scientific results through well-written manuscripts, grant proposals, and oral presentations.
4. Help build and maintain an environment promoting our core values: integrity, curiosity, persistence, teamwork, and innovation.
5. Respect and have fun with colleagues. We are here to have a great time while making discoveries!

At the Computational Omics | Huang Lab, you will focus on using Multi-Omics and Machine-Learning (ML) approaches to address key challenges in age-related human diseases, including Cancer and Neurodegeneration (ex. Alzheimer’s). Our team has established extensive networks in national consortia and internal/external collaborations, including unique DNA-Seq datasets for a million Mount Sinai individuals, that you can build upon for collaboration and career advancement opportunities. We welcome individuals from all backgrounds with relevant skill sets to apply and will consider specific research proposals.

Since 2020, the lab has established a hybrid work policy that ensures flexibility, productivity, and collaboration. We also offer competitive salaries (15K above NIH guidelines) and discounted postdoc housing in New York City

If you are interested, please send your CV, GitHub (or code), and demo of one project that you are proudest of (from any field) to


Open position: Ph.D./Master Students

We welcome inquiries from Ph.D. & Master students of the Graduate School of Biomedical Sciences at the Icahn School of Medicine at Mount Sinai (ISMMS)


Open position: Volunteers

We welcome scientists at all levels to collaborate with us. If you are at a high school, collegiate, or MD student level, please see the Science page to leverage the data science/computational biology learning materials that will enable you to contribute to biomedical breakthroughs. 

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