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Machine Learning Biomedical Internship information

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 are popular job titles related to Machine Learning Biomedical Internship jobs in Minnesota? For Machine Learning Biomedical Internship jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Machine Learning Biomedical Internship jobs in Minnesota look for? The top searched job categories for Machine Learning Biomedical Internship jobs in Minnesota are:
What cities in Minnesota are hiring for Machine Learning Biomedical Internship jobs? Cities in Minnesota with the most Machine Learning Biomedical Internship job openings:
Machine Learning Biomedical Internship jobs near you
Senior Principal AI/ML Engineer - Research Sovereign AI

Senior Principal AI/ML Engineer - Research Sovereign AI

Mayo Clinic

Rochester, MN

$175K - $263K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 22 days ago

Mayo Clinic rating

7.8

Company rating: 7.8 out of 10

Based on 680 frontline employees who took The Breakroom Quiz

134th of 873 rated healthcare providers

Job description

Why Mayo Clinic

Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans - to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.

Benefits Highlights
  • Medical: Multiple plan options.
  • Dental: Delta Dental or reimbursement account for flexible coverage.
  • Vision: Affordable plan with national network.
  • Pre-Tax Savings: HSA and FSAs for eligible expenses.
  • Retirement: Competitive retirement package to secure your future.

Responsibilities

Position Summary

The Senior Principal AI/ML Engineer  for AI Representation & EMR Vectorization is the senior technical leader and lead scientist responsible for architecting Mayo Clinic's unified multimodal EMR representation layer. This role defines and builds the scientific substrate used by foundational models, clinical agents, and research applications. The individual serves as a hands-on expert and player-coach, guiding technical strategy while contributing directly to model development, graph construction, and representation science. Over time, this position will build and lead a specialized team. 

Key Responsibilities

Scientific & Technical Leadership

  • Design and implement Mayo's multimodal EMR representation AI architecture, including text, imaging, waveform, structured data, temporal sequences, and multi-visit trajectories.
  • Develop graph-based representations and knowledge graphs linking patients, events, attributes, clinical concepts, and embeddings.
  • Integrate graph reasoning, vector similarity search, and hybrid vector-graph pipelines for retrieval-augmented models and agentic reasoning.
  • Define standards for temporal modeling, drift-aware embeddings, and sequence alignment across encounters.

Hands-On Modeling & Engineering

  • Build large-scale embedding pipelines using transformer-based models, contrastive learning, graph neural networks, and hybrid architectures.
  • Implement efficient query layers using vector stores and graph databases.
  • Develop interpretable embedding diagnostics, attribution tools, and graph-based audits to enable safe clinical use.
  • Explore and implement methods for explaining similarity, graph traversals, temporal evolution, and patient-neighborhood reasoning.

Cross-functional Collaboration

  • Work with AI researchers on specialty-specific embeddings, representation refinement, and research prototypes.
  • Collaborate with clinicians to operationalize clinically meaningful features, phenotypes, and longitudinal concepts.
  • Provide scientific input to the Foundational Model Science Program to ensure alignment between representations and model architectures.

Team Leadership

  • Serve as founding technical lead of the Reasoning EMR Representation team.
  • Mentor junior scientists and engineers; build a future team specializing in representation learning and graph-based reasoning.

Qualifications

Required

  • Master's in Computer Science, Machine Learning, Biomedical Engineering, or related field. 9 years of relevant experience, or a bachelor's degree with 11 years of relevant experience. 
  •  Extensive (9+ years) experience applying AI and machine learning in production healthcare environments or similar highly regulated or technology focused industries, showcasing an acute understanding of healthcare technology.
  • Hands-on expertise with graph databases, and knowledge graph construction.
  • Strong experience with transformer-based models, contrastive learning, and temporal modeling.

  • Experience designing or deploying vector search systems and hybrid vector-graph reasoning pipelines.

Preferred

  • PhD or Master's in Computer Science, Machine Learning, Biomedical Engineering, or related field.
  • 10+ years experience building production ML systems, including multimodal architectures and representation learning.
  • Experience with EMR data, healthcare multimodality, or clinical data integration.
  • Experience building patient similarity models, temporal embedding systems, or phenotype discovery pipelines.
  • Strong background in explainability, causality, or interpretable ML.
  • Prior experience in a player-coach or team-lead role.

Exemption Status
Exempt
Compensation Detail
Education, experience and tenure may be considered along with internal equity when job offers are extended.; $175,406-263,099 annually
Benefits Eligible
Yes
Schedule
Full Time
Hours/Pay Period
80
Schedule Details
Monday - Friday regular day hours
Weekend Schedule
none expected
International Assignment
No
Site Description
Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is. 

Equal Opportunity

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the 'EOE is the Law'.  Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

Recruiter
Jill SquierQualifications:

Required

  • Master's in Computer Science, Machine Learning, Biomedical Engineering, or related field. 9 years of relevant experience, or a bachelor's degree with 11 years of relevant experience. 
  •  Extensive (9+ years) experience applying AI and machine learning in production healthcare environments or similar highly regulated or technology focused industries, showcasing an acute understanding of healthcare technology.
  • Hands-on expertise with graph databases, and knowledge graph construction.
  • Strong experience with transformer-based models, contrastive learning, and temporal modeling.

  • Experience designing or deploying vector search systems and hybrid vector-graph reasoning pipelines.

Preferred

  • PhD or Master's in Computer Science, Machine Learning, Biomedical Engineering, or related field.
  • 10+ years experience building production ML systems, including multimodal architectures and representation learning.
  • Experience with EMR data, healthcare multimodality, or clinical data integration.
  • Experience building patient similarity models, temporal embedding systems, or phenotype discovery pipelines.
  • Strong background in explainability, causality, or interpretable ML.
  • Prior experience in a player-coach or team-lead role.

What Mayo Clinic employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Mayo Clinic logo

About Mayo Clinic

Sourced by ZipRecruiter

Mayo Clinic is the largest integrated, not-for-profit medical group practice in the world. We're building the future, one where the best possible care is available to everyone — and more people can heal at home. Our relentless research turns into earlier diagnoses and new cures. That's how we inspire hope in those who need it most. At Mayo Clinic, experts work together to solve the most challenging unmet needs of patients. Our history of innovation dates back almost 150 years, when brothers Will and Charlie Mayo pioneered an integrated, team-based approach to medicine. Today, that trailblazing spirit drives innovations like Mayo Clinic Platform — which powers new technologies to change how care is delivered to all.

Industry

Hospitals

Company size

10,000+ Employees

Headquarters location

Rochester, MN, US

Year founded

1919

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