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Medical Imaging Machine Learning Internship Phd Jobs

Instacart

OR

Overview We are looking for interns to join Instacart's Economics team. The ideal candidate for ... machine learning. We are in particular looking for current or recently graduated PhD students in ...

Natera

OR

PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics ... medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

As part of our machine learning team, you will play a vital role in prototyping foundational ... imaging applications.Experience with Pytorch. MS/PhD in computer vision, electrical, optical or ...

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Medical Imaging Machine Learning Internship Phd information

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$25.5K

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

As of Jun 12, 2026, the average yearly pay for medical imaging machine learning internship phd 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 is a Medical Imaging Machine Learning Internship for PhD students?

A Medical Imaging Machine Learning Internship for PhD students is a specialized training opportunity designed for doctoral candidates interested in applying advanced machine learning techniques to medical imaging data. Interns typically work on projects involving the development and validation of algorithms for tasks such as image segmentation, detection, diagnosis, or prognosis using modalities like MRI, CT, or X-ray. These internships are often hosted by hospitals, research labs, or tech companies and allow students to gain practical experience, collaborate with interdisciplinary teams, and contribute to innovations in healthcare technology. The experience can also help PhD students build a professional network and enhance their research portfolio.

What types of projects and collaborations can I expect during a Medical Imaging Machine Learning Internship as a PhD student?

As a PhD intern in Medical Imaging Machine Learning, you will typically work on projects involving the development and evaluation of deep learning models for tasks such as image segmentation, disease detection, or image enhancement. You will collaborate closely with multidisciplinary teams, including radiologists, data scientists, and software engineers, to translate research ideas into practical solutions. Interns often participate in regular team meetings, present findings, and are encouraged to contribute to publications or patents. This role provides valuable exposure to both academic and industry perspectives, offering opportunities for networking and skill development within a fast-evolving field.

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

To thrive in a Medical Imaging Machine Learning Internship as a PhD candidate, you need advanced knowledge of machine learning, computer vision, and medical image analysis, typically backed by a strong research background in related fields. Experience with programming languages (such as Python), deep learning frameworks (like TensorFlow or PyTorch), and familiarity with medical imaging data formats (e.g., DICOM) are essential. Strong problem-solving skills, collaboration, and effective scientific communication set top candidates apart. These competencies enable you to develop innovative solutions and contribute effectively to interdisciplinary healthcare technology teams.
Infographic showing various Medical Imaging Machine Learning Internship Phd job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% In-person 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

Posted 5 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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