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Bioinformatics Machine Learning Internship information

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$25.7K

$43K

$88.8K

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

As of Aug 7, 2026, the average yearly pay for bioinformatics machine learning internship in Hartford, CT is $42,955.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,800.00 and $46,400.00 per year, depending on experience, location, and employer.

What is a bioinformatics machine learning internship?

A Bioinformatics Machine Learning Internship is a temporary position, usually for students or recent graduates, where interns gain hands-on experience applying machine learning techniques to biological data. Interns may work on projects like analyzing genomic sequences, predicting protein structure, or developing algorithms for biomedical research. The role involves coding, data analysis, and collaborating with scientists to solve real-world biological problems. It offers exposure to both computational methods and biological sciences, preparing interns for careers in bioinformatics, data science, or research.

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

To thrive as a Bioinformatics Machine Learning Intern, you need a solid background in biology, statistics, and computer science, typically supported by relevant coursework or a degree in bioinformatics, computational biology, or a related field. Familiarity with programming languages like Python or R, experience using bioinformatics tools (e.g., BLAST, Bioconductor), and knowledge of machine learning frameworks such as TensorFlow or scikit-learn are highly valued. Attention to detail, problem-solving skills, and effective communication help interns collaborate on interdisciplinary teams and interpret complex datasets. These skills ensure interns can contribute meaningfully to research projects, derive insights from biological data, and communicate findings clearly.

What are some typical projects or tasks a bioinformatics machine learning intern might work on during their internship?

As a Bioinformatics Machine Learning Intern, you'll often contribute to projects that involve developing and testing algorithms for analyzing biological data, such as genomic sequences or protein structures. Typical tasks may include preprocessing large datasets, implementing machine learning models to identify patterns or make predictions, and visualizing results for team discussions. Interns frequently collaborate with both computational scientists and experimental biologists, gaining exposure to interdisciplinary teamwork and real-world applications. This hands-on experience helps interns build both technical and domain-specific skills, preparing them for advanced roles in bioinformatics or data science.

What is the difference between Bioinformatics Machine Learning Internship vs Bioinformatics Data Analyst Internship?

AspectBioinformatics Machine Learning InternshipBioinformatics Data Analyst Internship
Required SkillsProgramming, machine learning, bioinformatics toolsData analysis, statistical skills, bioinformatics tools
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch labs, healthcare, biotech firms
Industry UsageDeveloping algorithms, predictive models in bioinformaticsAnalyzing biological data, generating reports

While both internships involve bioinformatics, the Bioinformatics Machine Learning Internship focuses on developing machine learning models and algorithms, whereas the Bioinformatics Data Analyst Internship emphasizes analyzing biological data and generating insights. Both roles require programming and bioinformatics skills but differ in their core focus and application.

What are popular job titles related to Bioinformatics Machine Learning Internship jobs in Hartford, CT? For Bioinformatics Machine Learning Internship jobs in Hartford, CT, the most frequently searched job titles are:
What job categories do people searching Bioinformatics Machine Learning Internship jobs in Hartford, CT look for? The top searched job categories for Bioinformatics Machine Learning Internship jobs in Hartford, CT are:
Bioinformatics Machine Learning Internship jobs near you
Infographic showing various Bioinformatics Machine Learning Internship job openings in Hartford, CT as of July 2026, with employment types broken down into 5% As Needed, 76% Full Time, 13% Part Time, 3% Contract, 2% Nights, and 1% Summer. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $42,955 per year, or $20.7 per hour.

Fall 2026, Intern/Coop: Machine Learning Researcher

RTX Corporate

East Hartford, CT

Part-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago

RTX rating

8.2

Company rating: 8.2 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

38th of 72 rated aerospace companies

Job description

Date Posted:

2026-08-05

Country:

United States of America

Location:

US-CT-EAST HARTFORD-RTRC K ~ 411 Silver Ln ~ RTRC K

Position Role Type:

Hybrid

U.S. Citizen, U.S. Person, or Immigration Status Requirements:

Must be authorized to work in the U.S. without the company’s immigration sponsorship now or in the future. The company will not offer immigration sponsorship for this position.​ The company will not seek an export authorization for this role.

Security Clearance Type:

None/Not Required

Security Clearance Status:

Not Required
Job Description

Are you ready to explore the world of aerospace and defense? Do you want to learn from and collaborate with some of the greatest minds in the industry? At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on complex problems, advance your skills and create a safer, more connected world. Discover opportunities to make a difference at RTX.

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Join us and help shape the future of aerospace and defense.

The Artificial Intelligence team researches and develops machine learning, computer vision, reinforcement learning, large language models and human computer interaction solutions for a variety of high impact real world problems in the aerospace, manufacturing and defense industries. Examples include autonomy, multi-agent coordination, cybersecurity, material discovery and design. We conduct basic and applied research in a stimulating multi-disciplinary environment where scientists, engineers, practitioners, and subject matter experts collaborate and exchange experience.

We are looking for fall interns/coops to support research on large language models, with primary emphasis on agentic AI, reasoning models and verification/evaluation frameworks for LLMs and agentic systems.

What You Will Do:

  • Develop methods and algorithms to evaluate, verify, and improve the reasoning, planning, and decision making of large language models and LLM-based agents.

  • Design and run experiments on GPU cluster, and benchmark performance against established baselines.

  • Explore approaches for agentic AI, including LLM agents that can plan, reason, and interact with tools and environments in a safe and reliable manner.

  • Detect and mitigate vulnerabilities such as hallucinations and jailbreaks.

  • Communicate research findings through presentations, technical reports, and contributions to top-tier publications.

  • Collaborate with a focused team on topics including safe and reliable LLM deployment, vulnerability detection, and LLM agents, gaining exposure to cutting-edge Generative AI applications
     

What You Will Learn:

  • Gain exposure to advanced research on LLMs and agentic systems, including planning, tool use, and interaction within complex environments.

  • Strengthen hands-on skills in large-scale model training, evaluation, verification and safe deployment practices.

  • Learn how to communicate research results effectively through presentations, technical writing, and potential contributions to top-tier AI/ML conferences.
     

Qualifications You Must Have:

  • Currently pursuing an MS/Ph.D. in Computer Science, Mathematics, or a related Engineering discipline. Candidates must work a minimum of 6 months in co-op role. Please submit a copy of your academic transcripts with your application.

  • 1+ years of MS/Ph.D.-level research experience in areas such as large language models, reasoning, post-training/fine-tuning techniques, robustness/vulnerability detection, formal verification

  • 1+ years of machine learning software development experience in Python, with familiarity in deep learning frameworks such as PyTorch or TensorFlow.
     

Qualifications We Prefer:

  • Publication record in top AI/ML venues such as NeurIPS, ICML, ICLR, ACL, or similar.

  • Demonstrated ability to set research direction, work independently, and contribute to collaborative team efforts.

Please ensure the role type defined below is appropriate for your needs before applying to this role. This position is classified as:

Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.

Candidates will learn more about role type and current site status throughout the recruiting process. For onsite and hybrid roles, commuting to and from the assigned site is the employee’s personal responsibility.

As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.

The salary range for this role is 37,000 USD - 82,000 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company’s performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.

RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans’ Readjustment Assistance Act.

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