Postdoctoral Fellow in Spatial Biology

Icahn School of Medicine at Mount S; New York (NY); Presencial; USD 52.000 - 72.000; Jornada completa

Descripción de la vacante

The Icahn School of Medicine at Mount Sinai in New York City invites applications for a postdoctoral fellow to advance computational spatial biology research. The role focuses on developing quantitative, scalable ML/AI tools that integrate spatial multi-omics data with mechanistic tissue models.

The project includes collaboration with leading scientists to uncover mechanisms underlying cancer and neurodegenerative diseases, with opportunities for significant methodological and scientific

Formación

• PhD in a quantitative field with strong computational skills.
• Proven ability to analyze genomic data and apply ML methods.
• Experience with statistical programming and data interpretation.

Responsabilidades

• Develop scalable ML tools to integrate spatial multi-omics data with mechanistic models.
• Collaborate with scientists to investigate cancer and neurodegenerative disease mechanisms.

Conocimientos

Machine learning

Programming

Genomic data analysis

Analytical thinking

Educación

PhD in a quantitative field

Descripción del empleo

Description

The lab of Dr. Guo-Cheng Yuan in the Department of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai (ISMMS) in New York City is seeking a highly motivated postdoctoral fellow to conduct computational research in spatial biology.

The postdoc will play a central role in developing quantitative, flexible, and scalable machine learning and AI tools that integrate spatial multi-omics data with mechanistic models across molecular, cellular, and tissue scales. The postdoc will also have the opportunity to make major contributions to understanding the mechanisms underlying cancer and neurodegenerative diseases, through close collaboration with world-class scientists at ISMMS and beyond.

Qualifications

• PhD in a quantitative field
• Strong analytical, machine learning, and programming skills
• Prior experience analyzing genomic data (broadly defined)
• A record of first-author publications, including peer-reviewed papers or preprints
• Ability to work both independently and collaboratively
• Knowledge of spatial biology is desirable but not required. Experimentally trained candidates with strong statistical and programming skills are also encouraged to apply.