Research Intern

Posted 2 Days Ago
Be an Early Applicant
Paris, Île-de-France, FRA
Hybrid
Internship
Healthtech
The Role
Conduct machine learning research on X-ray, CT, and MRI foundation and vision-language models. Responsibilities include reviewing literature, proposing and testing approaches, training and evaluating models on large-scale medical imaging datasets using cloud and HPC infrastructure, contributing tested Python and PyTorch code, documenting experiments, presenting results, and collaborating with researchers and engineers. The internship lasts approximately six months in Paris under a French school internship agreement.
Summary Generated by Built In

The Research Intern joins the X-ray, CT, and MRI machine learning group for a six-month end-of-studies research internship in France. The group pre-trains foundation models on large-scale radiology data using cloud and HPC infrastructure and builds vision-language models for medical images. The final research subject is agreed before the internship starts and may include open-vocabulary grounding for chest X-ray vision-language models or a cross-modality foundation model spanning X-ray and CT. This is a fixed-term internship (stage) under a French internship agreement (convention de stage) with the student's school.

 

Essential Duties and Responsibilities 

 

  • Learn the clinical context for assigned modalities, including how images are acquired, how pathologies appear, and how radiologists read them.

  • Review relevant literature and propose approaches to test for the agreed research subject.

  • Train and evaluate models on large-scale medical imaging datasets using cloud and HPC infrastructure.

  • Compare results against baselines and report what worked and what did not.

  • Contribute tested code to the team's ML monorepo through code review.

  • Report progress weekly to the tutor and present results to the team.

  • Document the work so the team can build on it, and contribute to a publication where results allow.

  • Apply disciplined experimentation, including clear hypotheses, controlled comparisons, and critical reading of results.

  • Collaborate with researchers and engineers on the foundation-model and vision-language roadmap as assigned.

  • Follow DeepHealth data privacy, security, and research-integrity expectations when working with clinical imaging data.

 

 PLEASE NOTE: This is not an exhaustive list of all duties, responsibilities and requirements of the position described above.  Other functions may be assigned and management retains the right to add or change duties at any time.

Minimum Qualifications, Education and Experience

  • Final-year Master's or engineering school (grande ecole / ecole d'ingenieurs) student in machine learning, computer science, applied mathematics, or a related field, seeking a 6-month end-of-studies internship in France (required).

  • Must be eligible for a French internship (stage) under a school internship agreement (convention de stage) for the full internship period (required).

  • Strong machine learning fundamentals, including probability, linear algebra, and optimization (required).

  • Solid knowledge of deep learning for computer vision (required).

  • Proficiency in Python and PyTorch (required).

  • Hands-on experience training and debugging deep neural networks (required).

  • Readable, tested code that others can build on (required).

  • Disciplined experimentation: clear hypotheses, controlled comparisons, and critical reading of results (required).

  • Ability to work autonomously within a team and communicate clearly in English (required).

  • Preferred: Familiarity with self-supervised learning, vision-language, or multimodal models.

  • Preferred: Experience with medical imaging (DICOM, 3D volumes, large images).

  • Preferred: Experience training on GPUs, from a single GPU to multi-GPU cluster jobs.

  • Preferred: Familiarity with Linux and git.

  • Preferred: Familiarity with AI coding agents such as Claude Code or Codex.

Quality Standards

  • Communicates, cooperates, and consistently functions professionally and harmoniously with all levels of supervision, co-workers, visitors, and vendors.

  • Demonstrates initiative, personal awareness, professionalism and integrity, and exercises confidentiality in all areas of performance. 

  • Follows all local, regional and country laws concerning employment.

  • Follows all DeepHealth policies and procedures.

  • Follows data privacy, compliance, safety and confidentiality standards at all times.

  • Practices universal safety precautions.

  • Promotes good public relations on the phone and in person.

  • Adapts and is willing to learn new tasks, methods, and systems.

  • Reports to work regularly as scheduled; consistently punctual with respect to working hours, meal and rest breaks, and maintains satisfactory personal attendance in accordance with DeepHealth guidelines.

  • Completes job responsibilities in a quality and timely manner.

 

Travel

No regular travel is expected. Occasional visits to other team sites may be possible.

 

 Working Environment

  • Office / Hybrid. Paris, Ile-de-France, France.

  • On-site presence is required during the first months of the internship.

  • Fixed-term internship (stage) of approximately 6 months.

  • Subject to a French convention de stage with the student's educational institution.

  • Working time and internship stipend (gratification) follow applicable French internship rules and DeepHealth France internship practice.

  • Not a permanent employment contract (CDI/CDD).

Physical Demands

The employee must be able to perform the essential duties and responsibilities of the position, with or without reasonable accommodation.

 

Compensation:

1,500.00-2,500.00 EURO per month

Skills Required

  • Final-year Master's or engineering school student in machine learning, computer science, applied mathematics, or a related field
  • Seeking a six-month end-of-studies internship in France
  • Eligibility for a French internship under a school internship agreement for the full internship period
  • Strong machine learning fundamentals, including probability, linear algebra, and optimization
  • Solid knowledge of deep learning for computer vision
  • Proficiency in Python and PyTorch
  • Hands-on experience training and debugging deep neural networks
  • Readable, tested code that others can build on
  • Disciplined experimentation with clear hypotheses, controlled comparisons, and critical result analysis
  • Ability to work autonomously within a team and communicate clearly in English
  • Familiarity with self-supervised learning, vision-language, or multimodal models
  • Experience with medical imaging, including DICOM, 3D volumes, or large images
  • Experience training on GPUs, from single-GPU to multi-GPU cluster jobs
  • Familiarity with Linux and Git
  • Familiarity with AI coding agents such as Claude Code or Codex
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The Company
HQ: Pak Shek Kok
306 Employees

What We Do

DeepHealth is a wholly-owned subsidiary of RadNet, Inc. (NASDAQ: RDNT) and serves as the umbrella brand for all companies within RadNet’s Digital Health segment. DeepHealth provides AI-powered health informatics with the aim of empowering breakthroughs in care through imaging. Building on the strengths of the companies it has integrated and is rebranding (i.e., eRAD Radiology Information and Image Management Systems and Picture Archiving and Communication System, Aidence lung AI, DeepHealth and Kheiron breast AI and Quantib prostate and brain AI), DeepHealth leverages advanced AI for operational efficiency and improved clinical outcomes in lung, breast, prostate, and brain health. At the heart of DeepHealth’s portfolio is a cloud-native operating system – DeepHealth OS – that unifies data across the clinical and operational workflow and personalizes AI-powered workspaces for everyone in the radiology continuum. Thousands of radiologists at hundreds of imaging centers and radiology departments around the world use DeepHealth solutions to enable earlier, more reliable, and more efficient disease detection, including in large-scale cancer screening programs. DeepHealth’s human-centered, intuitive technology aims to push the boundaries of what’s possible in healthcare.

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