Postdoc: AI-Driven Cancer Genomics & Immunotherapy

CO2000 H. Lee Moffitt Cancer Center and Research Institute, Inc.; United States; On-site; USD 60,000 - 75,000; Full time

Job summary

Moffitt Cancer Center in Florida is recruiting a Postdoctoral Fellow for the ICON Lab within Biostatistics and Bioinformatics. The fellow will work on cancer genomics and biomarker discovery using AI and advanced bioinformatics, with access to interdisciplinary training across departments.

Responsibilities include discovering and validating predictive biomarkers from large omics datasets, developing ML methods, building visualization tools, and collaborating with clinicians and scientists across

Qualifications

• PhD in Bioinformatics, Computer Science, Computational Biology, Statistics/Biostatistics, Data Science, or related quantitative field.
• Strong programming skills in Python and R.
• Experience with AI and machine learning.
• Experience with processing and integration of multi-omics data including single-cell RNA-seq and spatial omics.

Responsibilities

• Discover and validate new predictive biomarkers using large-scale cancer omics datasets, including single-cell and spatial omics data.
• Develop and extend computational, statistical and machine learning methods to advance cancer clinical and translational research.
• Design and implement novel visualizing tools to facilitate interpretation of complex omics results.
• Collaborate with clinicians and scientists across Moffitt clinical and research programs.

Skills

Python

R

AI

Machine learning

Genomics

Biostatistics

Education

PhD in Bioinformatics

Job description

Moffitt Cancer Center in Florida is recruiting a Postdoctoral Fellow for the ICON Lab within Biostatistics and Bioinformatics. The fellow will work on cancer genomics and biomarker discovery using AI and advanced bioinformatics, with access to interdisciplinary training across departments.

Responsibilities include discovering and validating predictive biomarkers from large omics datasets, developing ML methods, building visualization tools, and collaborating with clinicians and scientists across