Senior Bioinformatics Lead: Multi-Omics & Cancer Genomics

University-of-Rochester; Center (TX); On-site; USD 97,000 - 146,000; Full time

Job summary

The University of Rochester invites applications for a leadership role in Radiation Oncology M&D to lead analysis of high-throughput multi-omic data, investigate tumor evolution and radiation-related phenotypes, and develop computational methods. The role integrates clinico-genomic and spatial-omics data using machine learning to study microenvironment dynamics under treatment.

You will direct bioinformatics operations, collaborate with faculty and clinicians, define program goals, oversee

Qualifications

• PhD and 3 years relevant experience or equivalent.
• Strong knowledge of data mining algorithms and machine learning techniques.
• Experience in cancer research, biology, and bioinformatics.
• Familiarity with next-generation sequencing analysis workflows.
• Proficiency in R and Python.

Responsibilities

• Leads complex multi-omic analyses to identify biomarkers of therapeutic resistance and generate patient-specific insights.
• Integrates clinico-genomic and spatial-omics data using machine learning and statistical methods to evaluate microenvironment dynamics under treatment.
• Directs bioinformatics operations and develops educational materials for highly technical cancer biology research.
• Collaborates with faculty, clinicians, bioinformaticians, and research partners nationally and internationally to advance multidisciplinary research initiatives.
• Defines program goals, resources, milestones, deliverables, and services; oversees program governance and strategy for growth.

Skills

Data mining

Machine learning

Statistics

R

Python

Education

PhD

Job description

The University of Rochester invites applications for a leadership role in Radiation Oncology M&D to lead analysis of high-throughput multi-omic data, investigate tumor evolution and radiation-related phenotypes, and develop computational methods. The role integrates clinico-genomic and spatial-omics data using machine learning to study microenvironment dynamics under treatment.

You will direct bioinformatics operations, collaborate with faculty and clinicians, define program goals, oversee