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Statistics Postdoc Jobs in Texas (NOW HIRING)

Tamus

Postdoctoral Research Associate

College Station, TX · On-site

$4.5K/mo

Job Title Postdoctoral Research Associate Agency Texas A&M Agrilife Research Department Institute ... Performs lab-based analysis of new and existing clinical samples, advanced statistical analysis of ...

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How much do statistics postdoc jobs pay per hour?

As of Aug 3, 2026, the average hourly pay for statistics postdoc in Texas is $31.13, according to ZipRecruiter salary data. Most workers in this role earn between $20.93 and $35.30 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in a statistics postdoc position, and why are they important?

To thrive as a Statistics Postdoc, you need an advanced degree (usually a Ph.D.) in statistics or a closely related field, with strong analytical, mathematical, and research skills. Familiarity with statistical software such as R, Python, SAS, or MATLAB, and experience in data management or computational modeling are typically expected. Excellent problem-solving skills, effective communication, and the ability to work collaboratively enhance your effectiveness in multidisciplinary research teams. These skills are important because postdoctoral researchers must generate rigorous scientific results while contributing to scholarly publications and advancing ongoing research projects.

What types of projects and collaborations can a statistics postdoc typically expect to be involved in?

As a Statistics Postdoc, you will likely contribute to a range of research projects, often partnering with faculty, graduate students, and professionals from diverse disciplines such as public health, engineering, or biology. These collaborations may involve developing new statistical methodologies, analyzing large or complex data sets, and publishing findings in peer-reviewed journals. You may also have opportunities to mentor junior researchers and present your work at conferences. This collaborative and dynamic environment offers valuable experience for building a strong academic or industry-focused research career.

What is a statistics postdoc?

A Statistics Postdoc is a temporary research position for individuals who have recently earned a Ph.D. in statistics or a related field. It typically involves conducting advanced research, developing new statistical methods, analyzing complex data, and collaborating with faculty and other researchers. Postdocs may also teach, publish papers, and contribute to grant writing. The position helps early-career researchers gain experience before pursuing faculty or industry roles.

What are popular job titles related to Statistics Postdoc jobs in Texas? For Statistics Postdoc jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Statistics Postdoc jobs in Texas look for? The top searched job categories for Statistics Postdoc jobs in Texas are:
Statistics Postdoc jobs near you
Infographic showing various Statistics Postdoc job openings in Texas as of July 2026, with employment types broken down into 7% Internship, 10% As Needed, 75% Full Time, 3% Part Time, 1% Temporary, and 4% Nights. Highlights an 95% Physical, and 5% Remote job distribution, with an average salary of $64,756 per year, or $31.1 per hour.

Postdoctoral Associate - AI for Brain Tumors

Baylor College of Medicine

Houston, TX • On-site

$62K/yr

Full-time

Re-posted 11 days ago

Baylor College of Medicine rating

8.0

Company rating: 8.0 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

183rd of 614 rated colleges and universities

Job description

Postdoctoral Associate - AI for Brain Tumors
Division: Neurosurgery
Work Arrangement: Onsite only
Location: Houston, TX
Salary Range: $62,232
FLSA Status: Exempt
Work Schedule: Monday - Friday, 8 a.m. - 5 p.m.
Summary
The Postdoctoral Associate will develop next-generation AI models for large-scale perturbation modeling in brain tumors. The project will involve building and applying state-of-the-art machine learning approaches, including foundation models, variational autoencoders (VAEs), and transformer-based architectures, to integrate single-cell and multi-omic datasets. The goal is to decode tumor cellular heterogeneity and tumor microenvironment interactions, and to identify targetable genes, pathways, and therapeutic strategies at single-cell resolution.
Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.
Job Duties
  • Develops and implements AI models for perturbation prediction:
    • Designs, trains, and evaluates machine learning models (e.g., transformer-based architectures, VAEs, and foundation models) to predict cellular responses to genetic and pharmacologic perturbations. This includes preprocessing large-scale single-cell and multi-omic datasets, defining model architectures, optimizing training pipelines on GPU clusters, and benchmarking against existing methods.
  • Integrate and analyze large-scale single-cell and multi-omic:
    • Processes and harmonizes scRNA-seq, scATAC-seq, and related datasets across brain tumor cohorts.
    • Performs downstream analyses such as cell state annotation, pathway enrichment, and tumor-tumor microenvironment interaction modeling to generate biologically meaningful insights.
  • Leads computational research projects and method development.
  • Performs other job-related duties as assigned.

Minimum Qualifications
  • MD or Ph.D. in Basic Science, Health Science, or a related field.
  • No experience required.

Preferred Qualifications
  • Ph.D. in Computational Biology, Bioinformatics, Computer Science or a related quantitative field.
  • Strong background in machine learning and statistical modeling, with experience in deep learning frameworks (e.g., PyTorch or TensorFlow). Familiarity with modern architectures such as transformers, variational autoencoders (VAEs), and foundation models is highly desirable.
  • Experience in analyzing large-scale genomics or single-cell datasets (e.g., scRNA-seq, scATAC-seq).
  • Proficiency in Python and experience with R/Seurat or Scanpy.
  • Strong skills in writing efficient, reproducible, and well-documented code.
  • Evidence of productivity through first-author publications or preprints in computational biology, machine learning, or related fields.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.
PD; SN
Requisition ID: 24929

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