Postdoc/Senior Scientist in Statistical Genomics / Omics-ML

Icahn School of Medicine at Mount Sinai
Genetics and Genomic Sciences
United StatesNYNew York
labs.icahn.mssm.edu/kuanhuanglab/

Description

We are recruiting postdoctoral scholars with expertise in genomics, computational biology, and computer/data science (labs.icahn.mssm.edu/kuanhuanglab/). 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 Alzheimer’s Disease, Cancer, and COVID-19. Our team has established extensive networks in national consortia and internal/external collaborations 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 options for hybrid/virtual meetings and onsite/remote work. We also offer competitive salaries (10K+ above NIH recommendation) and discounted postdoc housing in New York City.


Qualifications

PhD in genomics, computational biology, and computer/data science (or related fields)
Enthusiasm for teamwork and science communication
Lead-author or significant contribution to peer-reviewed research articles


Start date

As soon as possible

How to Apply

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 kuan-lin.huang [AT] mssm.edu