Deep Learning Intern

Study Association CognAC (SV CognAC); Netherlands; On-site; EUR 9,000 - 13,000; Full time

Job summary

Icare Finland Oy, part of Revenio Group, invites a Deep Learning Research Intern to collaborate with our team on AI models for ophthalmic image analysis. You will explore foundational models, self-supervised learning, and real-world radiology-type tasks in a medical imaging context.

The role involves working with deep learning engineers to build scalable experiments, using Kubeflow for reproducible pipelines, and evaluating various architectures.

Qualifications

• Currently pursuing or recently completed a degree in a relevant field with a focus on deep learning, machine learning, or computer vision.
• Proficient in Python with experience in deep learning frameworks (preferably TensorFlow).
• Solid understanding of deep learning concepts and evaluating model performance.
• Ability to critically analyse research papers and communicate findings clearly.

Responsibilities

• Conduct literature research to assess state-of-the-art practices.
• Work with large-scale ophthalmic imaging datasets, implementing self-supervised learning algorithms.
• Evaluate the impact of training paradigms, data, and model architectures on downstream tasks.
• Collaborate with other DL and DevOps engineers to set up pipelines using Kubeflow for reproducible experiments.

Skills

Python

TensorFlow

Deep learning

Research papers analysis

Communication

Education

Bachelor's or Master's in Computer Science, Electrical Engineering, Biomedical Engineering

Tools

Kubeflow

Job description

Position Summary

We are seeking a highly motivated Deep Learning Research Intern to join our team. As an intern, you
will work closely with our deep learning engineers to develop AI models for ophthalmic image analysis.

This role will provide you with the opportunity to explore advanced machine learning techniques, inclu-
ding foundational models and self-supervised learning, and contribute to real-world applications in me-
dical imaging. We particularly welcome candidates who are available for an internship placement wit-
hout a thesis combination.

Company Portrait

Icare Finland Oy is a part of Revenio Group Corporation, a public medtech company listed on the Hel-
sinki Stock Exchange. With our brand iCare we are a trusted partner in ophthalmic diagnostics, offering

physicians fast, easy-to-use, and reliable tools for diagnosis of glaucoma, diabetic retinopathy, and
macular degeneration. Our devices cover automated fundus imaging systems, perimeters, and
handheld rebound tonometers for human eyes. Our product assortment also includes IOP measuring
devices for veterinary use. iCare Solutions provide digital clinical tools that drive greater efficiency and enhance quality in eye care.

Key Responsibilities

• Conduct a literature research to assess state-of-the-art practices
• Work with large-scale ophthalmic imaging datasets, implementing self-supervised learning algo-
  rithms
• Evaluate the impact of different training paradigms, data, and model architectures on down-
  stream tasks
• In collaboration with other deep learning and DevOps engineers, set up pipelines using Kube-
  flow, ensuring reproducibility and scalability of experiments.

Qualifications & Experiences

• Educational Background
  • Currently pursuing or recently completed a Bachelor or Master in Computer Science,
    Electrical Engineering, Biomedical Engineering, or a related field, with a focus on deep
    learning, machine learning, or computer vision.
• Technical Skills:
  • Proficient in Python with experience in deep learning frameworks, preferably
    TensorFlow.
  • Solid understanding of deep learning concept
  • Skilled in critically analysing research papers
  • Experience in evaluating model performance
• Soft Skills:
  • Strong problem-solving abilities, capable of working both independently and
    collaboratively.
  • Effective communicator, able to explain technical concepts to non-experts and engage
    with clinical or DevOps experts.
  • Eager to learn new technologies and apply them to healthcare challenges
• Preferred Qualifications:
  • Experience in medical imaging, particularly ophthalmology.
  • Familiarity with machine learning pipeline management tools like Kubeflow.
  • Experience working with large-scale image datasets and preprocessing techniques.
  • Relevant experience with project-specific topics

Selection Process

• Application screening
• Conversational interview
• Live coding session
• Duration of internship: 4-6 Months
• Preferred: internship placement (not combined with thesis writing)
• Location: Toernooiveld 300, 6525 EC, Nijmegen with potentially 1-2 days per week remote