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Machine Learning Postdoc Jobs in Texas (NOW HIRING)

Tamus

Postdoctoral Research Associate

Corpus Christi, TX · On-site

$5.0K/mo

Job Title Postdoctoral Research Associate Agency Texas A&M University - Corpus Christi Department ... Documented scholarly achievements in applied statistics, machine learning, or deep learning (e.g ...

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Machine Learning Postdoc information

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$19.3K

$100.3K

$188.6K

How much do machine learning postdoc jobs pay per year?

As of Jul 7, 2026, the average yearly pay for machine learning postdoc in Texas is $100,252.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,007.00 and $138,071.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Postdoc position, and why are they important?

To thrive as a Machine Learning Postdoc, you need a deep understanding of machine learning algorithms, statistical modeling, and research methodology, typically supported by a completed PhD in a related field. Proficiency with programming languages like Python or R, experience with ML libraries (e.g., TensorFlow or PyTorch), and familiarity with large-scale datasets and cloud computing platforms are important. Strong analytical thinking, effective communication, and the ability to collaborate across multidisciplinary teams are standout soft skills in this position. These qualifications ensure innovative research contributions, successful project execution, and effective dissemination of findings in both academic and applied settings.

What is a Machine Learning Postdoc job?

A Machine Learning Postdoc is a research-focused position typically held after earning a Ph.D. in a related field. It involves conducting advanced research in machine learning, developing new algorithms, and publishing in top-tier conferences and journals. Postdocs often collaborate with faculty, industry partners, and other researchers to advance the state of the art in AI. The role may include mentoring students and contributing to grant proposals. It serves as a bridge between doctoral studies and a long-term academic or industry research career.

What are the typical responsibilities and collaborative aspects of a Machine Learning Postdoc position?

A Machine Learning Postdoc typically conducts original research, develops and tests new algorithms, and contributes to academic publications or patent applications. Daily tasks often involve data analysis, model building, and experimentation using advanced computational tools. Collaboration is key in this role, as postdocs frequently work alongside faculty, graduate students, and external industry partners to advance research objectives. Additionally, they may mentor junior researchers or students, present at conferences, and participate in grant writing or project planning. This mix of independent research and team collaboration fosters both professional growth and impactful scientific advancements.

What are the most commonly searched types of Machine Learning Postdoc jobs in Texas? The most popular types of Machine Learning Postdoc jobs in Texas are:
What are popular job titles related to Machine Learning Postdoc jobs in Texas? For Machine Learning Postdoc jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Postdoc jobs in Texas look for? The top searched job categories for Machine Learning Postdoc jobs in Texas are:
What cities in Texas are hiring for Machine Learning Postdoc jobs? Cities in Texas with the most Machine Learning Postdoc job openings:
Machine Learning Postdoc jobs near you
Infographic showing various Machine Learning Postdoc job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $100,252 per year, or $48.2 per hour.
Postdoctoral Associate - cancer epidemiology

Postdoctoral Associate - cancer epidemiology

Baylor College of Medicine

Houston, TX • On-site

Full-time

Posted 9 days ago

Baylor College of Medicine rating

8.6

Company rating: 8.6 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

54th of 544 rated colleges and universities

Job description

Summary

The Section of Epidemiology and Population Sciences at Baylor College of Medicine invites applications for a Postdoctoral Associate position for our Cancer Epidemiology with Real-World Data (RWD) Training Program. The Training Program provides epidemiology and bioinformatics Postdoctoral Associates with training in how to combine traditional epidemiologic research methods with RWD and modern technologies, like artificial intelligence and natural language processing, for impactful cancer research. Exciting opportunities also exist to work with faculty from MD Anderson Cancer Center, Rice University and UTHealth School of Biomedical Informatics. 

Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.

Job Duties
  • Analyzes large data sets.
  • Analyzes next generation sequencing data (e.g., RNA-seq, whole genome/ exome sequencing) to address complex biological and translational research questions.
  • Uses state-of-the-art bioinformatical and statistical tools.
  • Develops new statistical methods to answer biological questions that arise in the research.
  • Prepares manuscripts, abstracts, and presentations for peer-reviewed journals and scientific conferences.
  • Ensures compliance with institutional, sponsor and data security guidelines for handling sensitive genomic and clinical data.
  • Conducts advanced analysis of large-scale biomedical and population health datasets to support ongoing research within the section.
  • Collaborates with multidisciplinary teams that includes faculty investigators, statisticians, clinicians, and trainees, in a highly team-oriented research environment.
  • Participates in the Section's sponsored training program by contributing to collaborative projects, mentoring trainees, and engaging in programmatic activities such as seminars, workshops, and collaborative research initiatives.
  • Develops methodologies and tools for use in the electronic medical records that will strengthen the Learn Health System and improve patient outcomes.
  • 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 Epidemiology or Bioinformatics or related field.
  • Prior experience in analysis with real-world data, high-dimensional data, causal inference, and/or machine learning /artificial intelligence in a plus.
  • Knowledge in cancer biology or genetics is desired.
  • Excellent writing skills in English.
  • Ability to work in a team environment.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.

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