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Machine Learning Biomedical Internship Jobs in Bryan, TX

Tamus

Clinical Veterinarian

College Station, TX

... enriching the learning and working environment by promoting a culture that respects all ... Who we are The Texas A&M College of Veterinary Medicine & Biomedical Sciences (CVM ) is an ...

Tamus

Research Specialist

College Station, TX · On-site

$5.4K/mo

... to support biomedical research and data-driven discovery. Responsibilities * Analyzes and ... Familiarity with cloud computing, high-performance computing clusters, and machine learning methods.

All JobsMachine Learning Biomedical JobsMachine Learning Biomedical Internship JobsMachine Learning Biomedical Internship Jobs in Bryan, TX

Machine Learning Biomedical Internship information

See Bryan, TX salary details

$23.5K

$39.3K

$81.1K

How much do machine learning biomedical internship jobs pay per year?

As of Aug 11, 2026, the average yearly pay for machine learning biomedical internship in Bryan, TX is $39,266.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,000.00 and $42,400.00 per year, depending on experience, location, and employer.

What is a machine learning biomedical internship?

A Machine Learning Biomedical Internship is a temporary position where students or recent graduates work with professionals to apply machine learning techniques in the biomedical field. Interns typically assist with data analysis, model development, and research projects that involve biological or medical data. The goal is to gain practical experience in using artificial intelligence to solve healthcare challenges, such as disease prediction, medical imaging, or drug discovery. These internships often require knowledge of programming languages like Python and familiarity with machine learning frameworks. They provide valuable hands-on experience and networking opportunities for those interested in biomedical data science careers.

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

To excel as a Machine Learning Biomedical Intern, you need a solid background in computer science, statistics, and biology, often supported by coursework or a degree in related fields. Familiarity with programming languages like Python or R, experience with machine learning libraries (such as TensorFlow or scikit-learn), and knowledge of data analysis tools are typically required. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical concepts clearly are crucial soft skills. These competencies enable interns to develop effective models, collaborate with multidisciplinary teams, and contribute meaningful insights to biomedical research projects.

What types of projects do interns typically work on during a machine learning biomedical internship?

Interns in Machine Learning Biomedical roles often contribute to projects involving the development and validation of algorithms for analyzing medical data, such as imaging, genomics, or electronic health records. They may assist with data preprocessing, model training, and performance evaluation under the guidance of experienced researchers or engineers. Collaboration is common, as interns often work closely with interdisciplinary teams including data scientists, clinicians, and software engineers. This hands-on experience provides valuable exposure to real-world biomedical challenges while strengthening both technical and communication skills.
What job categories do people searching Machine Learning Biomedical Internship jobs in Bryan, TX look for? The top searched job categories for Machine Learning Biomedical Internship jobs in Bryan, TX are:
What cities near Bryan, TX are hiring for Machine Learning Biomedical Internship jobs? Cities near Bryan, TX with the most Machine Learning Biomedical Internship job openings:
Machine Learning Biomedical Internship jobs near you
Infographic showing various Machine Learning Biomedical Internship job openings in Bryan, TX as of June 2026, with employment types broken down into 34% Internship, 33% Part Time, and 33% Temporary. Highlights an 100% In-person job distribution, with an average salary of $39,266 per year, or $18.9 per hour.

Postdoctoral Research Associate

Texas Agricultural Experiment Station

College Station, TX • Hybrid

$4.1K/mo

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 28 days ago

Job description

Job Title

Postdoctoral Research Associate

Agency

Texas A&M Agrilife Research

Department

Plant Pathology & Microbiology

Proposed Minimum Salary

$4,166.67 monthly

Job Location

College Station, Texas

Job Type

Staff

Job Description

AboutTexas A&M AgriLife

Texas A&M AgriLife is comprised of the following Texas A&M University System members:

  • Texas A&M AgriLife Extension Service

  • Texas A&M AgriLife Research

  • College of Agriculture and Life Sciences at Texas A&M University

  • Texas A&M Forest Service

  • Texas A&M Veterinary Medical Diagnostic Laboratory

As thenation'slargestmostcomprehensive agriculture program, Texas A&M AgriLife brings together a college and four state agencies focused on agriculture and life sciences within The Texas A&M University System.With over 5,000 employees and a presence in every county across the state, Texas A&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service.

Clickhereto learn more about howyoucan be a part of AgriLife and make a difference in the world!

PositionInformation

The Antony-Babu laboratory seeks a Postdoctoral Research Associate to lead the field pathology and pathogen genomics of a project building predictive tools for cotton soil-borne disease management. The work is supported through a cooperative agreement with USDA-ARS and is conducted in collaboration with the USDA-ARS Southern Plains Agricultural Research Center (Insect Control and Cotton Disease Research Unit).This is a field scientist's role with full ownership of the genomics that flows from it. You will take the major cotton soil-borne pathogens from field and greenhouse experimentation through isolate sequencing, hybrid genome assembly, comparative and population genomics, and diagnostic-tool development, and you will publish the resulting population-ecology and disease biology. The position works alongside a Ph.D. student across the whole project. We are looking for someone who is independent in field-based research and in molecular bioinformatics, and who sees genome data and disease ecology as one continuous line of work rather than separate specialties.

Research Focus
You will lead the field pathology and pathogen genomics: design and run field and greenhouse pathogen experiments, drive the isolate-to-assembly-to-diagnostic-assay pipeline, and lead population-ecology and disease publications built on that genomic work.

Responsibilities:

  • Design and execute field and controlled-environment pathology experiments, including inoculum-density gradient studies; direct undergraduate research interns during field-sampling campaigns.
  • Lead hybrid (Oxford Nanopore + Illumina) sequencing, assembly, and annotation of pathogen genomes; conduct comparative and population genomics to characterize spatial/temporal structure, virulence, and effector variation, and to identify diagnostic target regions.
  • Translate genomic targets into field-deployable molecular diagnostics (LAMP), with quantitative cross-validation by droplet digital and real-time PCR.
  • Contribute to the host-microbiome analyses (GWAS/mGWAS, metagenomics) and the integrative modeling led by the graduate student.
  • Apply machine-learning and AI-assisted tools in genome analysis, population and disease-ecology work, and pipeline development, with attention to reproducibility and validation of results.
  • Develop reproducible bioinformatic pipelines on Texas A&M HPRC resources; prepare data, figures, and first- and co-authored manuscripts.
  • Maintain accurate lab records in both digital and hardcopy form, and ensure up-to-date lab safety documentation.
  • Lead and co-author manuscripts in scientific journals; assistance may also be sought in drafting extension documents.
  • Mentor the graduate students and interns.
  • Collaborate with USDA-ARS scientists.

Required Qualifications:

  • Ph.D. (in hand by start date) in plant pathology, microbiology, microbial/molecular genomics, agronomy/crop science with a pathology focus, or a related field.

Preferred Qualifications:

  • Demonstrated field and/or greenhouse experimental experience in plant pathology or a closely related discipline.
  • Demonstrated bioinformatics capability: microbial/fungal genome assembly and annotation, comparative or population genomics, command-line work in a Linux/HPC environment, and scripting in at least one of Python, R, or Bash.
  • Hands-on molecular biology (DNA extraction, library preparation, PCR/qPCR).
  • Experience handling Oxford Nanopore (ONT) sequence data.
  • A record of scientific productivity appropriate to career stage and strong written and oral communication.
  • As a field-demanding position, a current driver's license is required. The laboratory works with machine-learning and AI-assisted tools as part of routine research practice. Prior formal experience is not required, but candidates are expected to use these tools in their work and to develop fluency with them on the job, with a strong emphasis on reproducibility and validation.
  • Experience with soil-borne pathogens of cotton or other row crops (fungal and nematodes).
  • Population genomics, microbiome analysis, or diagnostic assay (LAMP/qPCR/ddPCR) development.
  • Field-trial design and prior mentoring or supervisory experience.

Additional Requirements:

  • Ability to obtain a valid US driver's license.
  • Initial one-year appointment, renewable up to four years contingent on performance and funding.

Knowledge, Skills, and Abilities:

  • Aseptic microbiology: both conceptual and demonstrable technical knowledge.
  • Microbial culture of bacteria and fungi; ability to grow microorganisms in pure culture and in interaction studies, including the soil-borne pathogens central to this project.
  • A deep understanding of the microbial species concept is mandatory, and is expected to inform the pathogen population-genomics and diagnostic work.
  • Ability to collect phenotypic data from plants (healthy, infected, and infested) in field and greenhouse settings.
  • Fast learner and self-starter, able to work independently.
  • Meticulous record-keeping and a detail-oriented approach.
  • Knowledge of laboratory maintenance and equipment.
  • Ability to multi-task and to work cooperatively with others across internal and external collaborations.
  • Experience in handling ONT data is required, and hands-on experience in running the Oxford Nanopore sequencer is desirable.
  • Experience in high-throughput culturomics is desirable.
  • Experience in, or interest in, laboratory automation will be an advantage.

Equipment used to perform the essential duties of this position:

Computer - 5 to10 hours/week

PCR machine - 5 to 10 hours/week

Sequencer - 5 to 10 hours/week

Why Work at Texas A&M AgriLife?

When you choose toworkfor Texas A&M AgriLife, you become part of an organization that is an established leader in agriculture and life sciences with a wide range of capabilities to meet the needs of our statewide, national, and international constituents.

In addition, Texas A&M AgriLife offers a comprehensive benefit packageincluding the following:

  • Health, dental, vision, life and long-term disability insurancewith Texas A&M AgriLife contributing to employee health and basic life premiums

  • 12-15 days of annual paid holidays

  • Up to eight hours of paid sick leaveand at leasteight hours of paid vacation each month

  • Automatic enrollment in theTeacher Retirement System of Texas

  • Employee Wellness Initiative for Texas A&M AgriLife

ApplicantInstructions

Applications received by Texas A&MAgriLifemust either have all job application data entered or a resume attached. Failure to provide all job application data or a complete resume could result in an invalid submission and a rejected application. We encourage all applicants to upload a resume or use a LinkedIn profile to prepopulate the online application.

RequiredDocuments

CV/ Resume

Cover letter

List of references

Certifications/additional documentation

All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution's verification of credentials and/or other information required by the institution's procedures, including the completion of the criminal history check.

Equal Opportunity/Veterans/Disability Employer.

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