Senior Scientist, Genomics & Multi-Omics for Autism

Convergenz; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Convergenz seeks a Senior Scientist in Genomics & Computational Biology to lead investigations into autism trajectories through genetics, epigenomics, metabolomics, and neuroimaging data. You will guide study design, measurements, and data integration across multi-cohort datasets.

The role emphasizes advanced data analysis, reproducible methods, and collaboration with cross-functional teams to inform budgets and project milestones for translational research.

Qualifications

• Experience in human genetics/genomics or other omics research (sequencing, epigenomics, transcriptomics, proteomics, metabolomics, microbiome) is required.
• Experience with computational methods for high-dimensional biological data: bioinformatics, statistical genetics, data science, computational modeling, and/or machine learning.
• Experience with large human cohorts or long-term datasets combining several data types.
• Experience with budgeting and program or project management.

Responsibilities

• Provide internal subject matter expertise on factors behind autism trajectories including genetics, epigenetics, metabolomics, immune profiling, microbiome, environmental exposures, and developmental history.
• Assess conceptual and technical soundness of proposed approaches; advise on study design, measurement choices, batch effects, and data handling.
• Help set goals, budgets, milestones for TA1 projects and coordinate with TA2/TA3 for data integration and target identification.

Skills

Genomics

Bioinformatics

Data science

Machine learning

Cohort analysis

Budgeting

Project management

Education

PhD in human genetics/genomics or related

Master’s degree with substantial relevant research

Job description

Convergenz seeks a Senior Scientist in Genomics & Computational Biology to lead investigations into autism trajectories through genetics, epigenomics, metabolomics, and neuroimaging data. You will guide study design, measurements, and data integration across multi-cohort datasets.

The role emphasizes advanced data analysis, reproducible methods, and collaboration with cross-functional teams to inform budgets and project milestones for translational research.