The Huang lab at the Icahn School of Medicine at Mount Sinai (ISMMS) is recruiting a Postdoc with expertise in Statistical Genomics, Multi-Omics, and Machine Learning. A Senior Scientist may also be granted to individuals showing extraordinary qualifications.
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 critical 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 WES/WGS datasets for a million Mount Sinai individuals with matched omics/EHR data, 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 ensuring flexibility, productivity, and collaboration for in-person and remote meetings. The lab also offers generous stipend that is at least 15k above NIH minimum and subsidized ISMMS postdoc housing in NYC.
Ph.D. in genomics, computational biology, and computer/data science (or related fields)
Enthusiasm for teamwork and science communication
Lead-author or significant contributions to peer-reviewed research articles in related fields
If you are interested, please send your CV, GitHub (or code), and one project that you are proudest of (from any field) to kuan-lin.huang [at] mssm.edu