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Machine Learning Biomedical Internship Jobs in Bryan, TX

TEES

Research Engineer I

College Station, TX

The Research Assistant will support the development and implementation of machine learning ... biomedical imaging, and photonics and semiconductors, with ML/AI infused in several of these ...

Tamus

Research Engineer I

College Station, TX · On-site

The Research Assistant will support the development and implementation of machine learning ... biomedical imaging, and photonics and semiconductors, with ML/AI infused in several of these ...

Tamus

Clinical Veterinarian

College Station, TX · On-site

... 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

$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 Sep 2, 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 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 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 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.

Research Engineer I

TEES

College Station, TX

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago

Job description

Job Title

Research Engineer I

Agency

Texas A&M Engineering

Department

Electrical Engineering

Proposed Minimum Salary

Commensurate

Job Location

College Station, Texas

Job Type

Staff

Job Description

Why work for Texas A&M Engineering?

Engineering has been part of Texas A&M University since its opening in 1876 as the Agricultural and Mechanical College of Texas. Today, the College of Engineering is the largest college on the College Station campus with more than 25,000 engineering students enrolled in 15 departments. Its mission is to serve Texas, the nation and the global community by providing engineering graduates who are well-founded in engineering fundamentals, instilled with the highest standards of professional and ethical behavior, and prepared to meet the complex technical challenges of society.

As the research arm of Engineering, the Texas A&M Engineering Experiment Station (TEES) is a state agency within the Texas A&M University System with a mission to improve lives through basic and applied engineering research, workforce development and technology transition. Our collaborations with industry, academia and government provide cutting-edge solutions to global technical challenges.

We are deeply committed to recruiting and retaining a talented workforce that embraces our core values of Respect, Excellence, Leadership, Loyalty, Integrity, and Service, by offering competitive salaries, an array of benefits, an extensive support network, and above all, an enriching and highly collaborative working community that is deeply passionate about our vision for higher education, research, and public service.

Job Description


The Research Assistant will support the development and implementation of machine learning algorithms for cyber-physical attack detection in electric power systems. Responsibilities include designing real-time analytics using Python and TensorFlow, reporting research findings, and contributing to collaborative research efforts. The position applies advanced skills developed during doctoral research in AI-enabled cybersecurity for power systems.

Responsibilities:

  • Support the development and implementation of machine learning algorithms for cyber-physical attack detection in electric power systems.

  • Design and implement real-time analytics using Python and TensorFlow.

  • Conduct research related to AI-enabled cybersecurity for electric power systems.

  • Analyze research data and report findings through technical documentation and presentations.

  • Contribute to collaborative research projects and support research team initiatives.

  • Apply advanced knowledge and skills developed through doctoral research in artificial intelligence and power systems cybersecurity.

What We Need:

  • Bachelors Degree

What is Helpful:

  • Bachelor's degree in Electrical Engineering, Computer Science, or a related field.

  • Master's or PhD in Electrical Engineering, Computer Science, or related discipline.

  • Research experience in machine learning, power systems, or cybersecurity.

  • Proficiency in Python programming.

  • Familiarity with machine learning frameworks (e.g., TensorFlow).

  • Understanding of electric power systems and cybersecurity concepts.

  • Strong analytical and problem-solving skills.

  • Ability to work collaboratively in a multidisciplinary research environment.

Equipment utilized:

  • Python development environments

  • Virtual Machines

  • Standard office and research equipment

Work Location:

  • Main Campus - College Station, TX.

About Electrical and Computer Engineering

The Department of Electrical and Computer Engineering at Texas A&M University leads advanced research in several important national and global areas for the betterment of humanity. Areas of research include power and power electronics, information systems, computer architecture, analog and mixed signals circuits, biomedical imaging, and photonics and semiconductors, with ML/AI infused in several of these research areas. Situated conveniently in the hub of the Dallas-Austin-Houston technology triangle, the department collaborates closely with key players in healthcare, computing, telecommunications, energy, and semiconductor manufacturing sectors. It also benefits from its proximity to and engagement with the Army Futures Command and the facilities and test-beds available at the Texas A&M System's RELLIS Campus. With strong support from Texas' robust manufacturing sector and its economy, the department has numerous opportunities to engage in exciting interdisciplinary research partnerships that are shaping the future educational and research landscapes. These partnerships include collaborations and engagement with the Texas A&M Data Science Institute, the Global Cyber Research Institute, the Texas A&M Energy Institute, and the Smart Grid Center.

Texas A&M Engineering provides an outstanding benefits package including but not limited to:

  • Competitive medical insurance benefits through Blue Cross and Blue Shield of Texas and Prescription coverage by Express Scripts.

  • Options for Vision, Dental, Life, and Long-Term Disability insurance.

  • A defined benefit retirement plan with the Teacher Retirement System of Texas (TRS) with 8.25% employer contribution.

  • Additional Voluntary Retirement Programs: Tax Deferred Account 403(b) and a Deferred Compensation Program 457(b).

  • Flexible spending account options for medical and childcare expenses

  • Generous paid time off with holidays, vacation and sick leave.

  • Robust free training access through LinkedIn Learning plus professional development opportunities.

  • Tuition assistance and Educational release time to further your academic pursuits.

  • Access to Engineer Your Wellness programs that provide opportunities for employees to engage in health and fitness.

  • Wellness release time offered to employees to promote work/life balance.

Helpful Applicant Information

Required Materials for Application:

  • Resume/CV

  • Three work references with their contact information; at least one reference should be from a supervisor/former supervisor.

  • Letter of interest

Applications received by Texas A&M Engineering must have all required job application data entered.

Failure to provide all job application data could result in an invalid submission and a rejected application.

Compensation Philosophy:

  • Recruit and retain a high-performing workforce through competitive compensation and career development including career pathing, coaching and skills development.

  • Recognize and reward exceptional performance based on individual and team contributions to the growth and success of Texas A&M Engineering.

  • Offer total rewards through flexible benefits, professional development, and work-life balance. Maintain an equitable and transparent process for compensation decisions.

  • Support, reinforce, and align compensation decisions with budgetary and financial strategies to ensure growth and sustainability.

Employment Eligibility Verification

  • If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in delay of start date.

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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