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How much do biomedical machine learning jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for biomedical machine learning in Dallas, TX is $28.22, according to ZipRecruiter salary data. Most workers in this role earn between $24.04 and $31.88 per hour, depending on experience, location, and employer.

What is a biomedical machine learning?

A Biomedical Machine Learning job involves developing and applying machine learning algorithms to analyze biomedical data for healthcare and research applications. Professionals in this field work with medical imaging, genomics, electronic health records, and wearable device data to improve disease diagnosis, treatment, and patient outcomes. They collaborate with researchers, clinicians, and data scientists to design predictive models and extract insights from complex biological data. This role requires expertise in machine learning, data processing, and domain-specific knowledge in healthcare or life sciences.

What does a biomedical machine learning do?

A typical day in Biomedical Machine Learning involves cleaning and preparing biomedical datasets, developing or refining machine learning models, running experiments, and interpreting results in collaboration with domain experts such as bioinformaticians and clinicians. Professionals often participate in team meetings to discuss project goals, share insights, and adjust research directions based on feedback. The role may also involve reading scientific literature to stay current with new methodologies and contributing to academic publications or technical documentation. Working closely with both technical and healthcare-focused colleagues, you'll help translate data-driven insights into meaningful biomedical solutions that impact patient care or research outcomes.

What are the key skills and qualifications needed to thrive in biomedical machine learning, and why are they important?

To thrive in Biomedical Machine Learning, you need a solid background in statistics, machine learning, programming (Python or R), and a strong understanding of biological or medical data, often supported by advanced degrees in computer science, biomedical engineering, or related fields. Experience with frameworks like TensorFlow, PyTorch, and familiarity with biomedical datasets is highly valued, and certifications in data science or biomedical informatics can be advantageous. Strong analytical thinking, communication skills, and the ability to collaborate with interdisciplinary teams are crucial soft skills. These competencies are vital to developing robust models that address complex healthcare challenges while ensuring scientific rigor and regulatory compliance.

What are the most commonly searched types of Biomedical Machine Learning jobs in Dallas, TX?

The most popular types of Biomedical Machine Learning jobs in Dallas, TX are:

What are popular job titles related to Biomedical Machine Learning jobs in Dallas, TX?

For Biomedical Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Biomedical Machine Learning jobs in Dallas, TX look for?

The top searched job categories for Biomedical Machine Learning jobs in Dallas, TX are:

Biomedical Machine Learning jobs near you
Infographic showing various Biomedical Machine Learning job openings in Dallas, TX as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $58,694 per year, or $28.2 per hour.

POSTDOCTORAL RESEARCHER-Biomedical Data Science & AI-Epidemiology-Ruan Lab [Req#: 963199, Position#:

UT Southwestern Medical Center

Dallas, TX • On-site

Full-time

Posted 13 days ago

UT Southwestern rating

7.9

Company rating: 7.9 out of 10

Based on 152 frontline employees who took The Breakroom Quiz

107th of 888 rated healthcare providers

Job description

Description
POSTDOCTORAL RESEARCHER
A postdoctoral fellow position is now available in the laboratories of Dr. Peifeng Ruan (https://qbrc.swmed.edu/labs/ruanlab/) at the Quantitative Biomedical Research Center (QBRC) in the Peter O'Donnell Jr. School of Public Health at UT Southwestern Medical Center, Dallas. The labs' research focuses on developing and applying advanced computational and AI methods to address critical challenges in biomedical research and clinical practice.
The training activities of this position will include data management, curation, and analysis of large-scale biomedical and clinical datasets, including proteomics, metabolomics, single-cell transcriptomics and spatial transcriptomics data; development and/or implementation of novel statistics, machine learning and AI approaches; integration of molecular, cellular, spatial, imaging, and clinical data; interpretation and presentation of analysis results; and writing manuscripts. We are actively seeking exceptionally motivated individuals with outstanding problem-solving abilities. In this role, you will conduct cutting-edge research at the intersection of artificial intelligence and biomedical sciences, with opportunities to collaborate with clinical investigators and industry partners.
Information on our postdoctoral training program, benefits, and a virtual tour can be found at https://www.utsouthwestern.edu/research/postdoctoral-scholars/.
Qualifications
Candidates with a Ph.D. in computer science, bioinformatics, data science, machine learning, or a related quantitative field are encouraged to apply. Experience with one or more of the following areas is desirable: single-cell transcriptomics and spatial transcriptomics, knowledge graphs, large language models, or analysis of real-world clinical data (e.g., electronic health records, claims databases, or pharmacovigilance databases).
Application Instructions
Interested individuals should send a CV and a list of three references to:
Peifeng Ruan
Peifeng.Ruan@UTSouthwestern.edu

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