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Medical Machine Learning Internship Jobs (NOW HIRING)

Jane Street

Machine Learning Engineer

New York, NY · On-site

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Jane Street

Machine Learning Engineer

New York, NY

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Corning

... on academic, internship, personal, or professional projects. - Strong Python foundation and hands-on experience with at least one machine learning library or framework such as scikit-learn ...

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Yaskawa

Machine Learning Engineer

Franklin, WI · On-site

To be successful you should have 0-3 years of of professional or internship experience in machine learning, data science, or software engineering. Also proficiency in Python and familiarity with ML ...

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Medical Machine Learning Internship information

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$25.5K

$42.6K

$88K

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

As of Jul 14, 2026, the average yearly pay for medical machine learning internship in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What kinds of projects and responsibilities can I expect during a Medical Machine Learning Internship?

As a Medical Machine Learning Intern, you'll typically work on real-world datasets to develop, test, and refine machine learning models aimed at improving healthcare outcomes. Your daily tasks may include data preprocessing, feature engineering, model selection, and performance evaluation under the guidance of experienced data scientists or clinicians. Collaboration is key, as you'll often work with multidisciplinary teams, including software engineers, clinicians, and researchers. This hands-on experience allows you to gain practical skills and contribute to impactful projects that can enhance patient care or medical research.

What are the key skills and qualifications needed to thrive as a Medical Machine Learning Intern, and why are they important?

To thrive as a Medical Machine Learning Intern, you need a solid background in statistics, programming (Python or R), and foundational knowledge of machine learning algorithms, typically supported by coursework or a relevant degree in computer science, engineering, or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience working with medical datasets or healthcare IT systems are highly valued. Strong analytical thinking, attention to detail, and effective communication skills will help you collaborate with interdisciplinary teams and present findings clearly. These skills are crucial for developing accurate, impactful models that address real-world healthcare challenges and ensure patient safety.

What is a Medical Machine Learning Internship?

A Medical Machine Learning Internship is a temporary position where students or recent graduates work on projects that apply machine learning techniques to healthcare and medical datasets. Interns typically collaborate with data scientists, clinicians, and researchers to develop algorithms that can assist in diagnosing diseases, predicting patient outcomes, or improving healthcare processes. This role provides hands-on experience with real-world medical data, exposure to regulatory considerations, and the opportunity to contribute to impactful healthcare innovations. Such internships help interns build technical and domain-specific skills, preparing them for future careers in medical data science.
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Medical Machine Learning Internship jobs near you
Infographic showing various Medical Machine Learning Internship job openings in the United States as of July 2026, with employment types broken down into 9% Internship, 1% As Needed, 68% Full Time, 20% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Machine Learning Internship - PhD: 2027

Machine Learning Internship - PhD: 2027

Susquehanna International Group, LLP

Philadelphia, PA • On-site

Full-time, Internship

Re-posted 6 days ago

Job description

Overview
Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.
As a Machine Learning Intern at Susquehanna, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You'll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.
What You Can Expect
  • Conduct research and develop ML models to identify patterns in noisy, non-stationary data
  • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • One-on-one mentorship from experienced researchers and technologists
  • Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for
  • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
  • Proven experience applying machine learning techniques in a professional or academic setting
  • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
  • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow
  • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?
  • Work with a world-class team of researchers and technologists
  • Access to unparalleled financial data and computing resources
  • Opportunity to make a direct impact on trading performance
  • Collaborative, intellectually stimulating environment with global reach

About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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