Postdoctoral Research Fellow - School of Public Health

Postdoctoral Research Fellow

We are looking for a Full-Time Postdoctoral Research Fellow to join UTHealth School of Public Health in Houston, TX. In this role you will focus on developing and applying statistical and computational methods to analyze both single-cell and bulk multi-omics data. The primary objective is to extract biologically meaningful insights at cell-type resolution and to advance our understanding of complex genomic mechanisms.

This position would support the Department of Biostatistics & Data Science, as well as the Center for Spatial-Temporal Modeling for Applications in Population Sciences.

What we do here changes the world. UTHealth Houston is Texas' resource for healthcare education, innovation, scientific discovery, and excellence in patient care. That's where you come in.

Once you join us you won't want to leave. It's because we reward our team for the excellent service they provide. Our total rewards package includes the benefits you'd expect from a top healthcare organization (benefits, insurance, etc.), plus:

• 100% paid medical premiums for our full-time employees
• Generous time off (holidays, preventative leave day, both vacation and sick time – all of which equates to around 37-38 days per year)
• The longer you stay, the more vacation you'll accrue!
• Build your future with our awesome retirement/pension plan!

We take care of our employees! As a world-renowned institution, our employees' wellbeing is important to us. We offer work/life services such as...

• Free financial and legal counseling
• Free mental health counseling services
• Gym membership discounts and access to wellness programs
• Other employee discounts including entertainment, car rentals, cell phones, etc.
• Resources for child and elder care
• Plus many more!

Position Summary:

We are looking for a Full-Time Postdoctoral Research Fellow to join UTHealth School of Public Health in Houston, TX. A postdoctoral position provides the opportunity to conduct cutting-edge research in statistical bioinformatics and statistical genomics. The successful candidate will focus on developing and applying statistical and computational methods to analyze both single-cell and bulk multi-omics data. The primary objective is to extract biologically meaningful insights at cell-type resolution and to advance our understanding of complex genomic mechanisms.

This position would support the Department of Biostatistics & Data Science and the Center for Spatial-Temporal Modeling for Applications in Population Sciences.

Position

Key Accountabilities:

• Develops novel statistical and computational methods for analyzing high-dimensional single-cell and bulk multi-omics datasets, with emphasis on cell-type-specific inference.
• Designs and carries out research studies to investigate genomic and epigenomic mechanisms using advanced modeling strategies.
• Collaborates with interdisciplinary teams, including statisticians, computational biologists, and biomedical researchers, to support ongoing research projects.
• Presents research findings at lab meetings, institutional seminars, and scientific conferences; prepares manuscripts for peer-reviewed publications.
• Mentors graduate students and trainees in methodological development and data analysis
• Stays current with scientific literature in genomics, biostatistics, and machine learning; contributes to proposal writing and idea development for future research.
• Implements reproducible workflows using open-source programming languages (e.g., R, Python) and version control tools (e.g., Git).
• Participates in collaborative grant writing and contributes to the preparation of progress reports and project deliverables.
• Performs other duties as assigned.

Preferred Qualifications:

• Proficiency in statistical programming languages such as R and Python
• Strong foundation in statistical modeling, machine learning, and high-dimensional data analysis
• Experience with genomic and epigenomic datasets, especially single-cell and bulk multi-omics data
• Familiarity with bioinformatics pipelines and tools
• Ability to work independently and collaboratively in multidisciplinary research teams

Minimum Education:

• Doctoral/Terminal Degree

Physical Requirements:

Exerts up to 20 pounds of force occasionally and/or up to 10 pounds frequently and/or a negligible amount constantly to move objects.

Security Sensitive:

This job class may contain positions that are security sensitive and thereby subject to the provisions of Texas Education Code § 51.215

Residency Requirement:

Employees must permanently reside and work in the State of Texas.