Research Engineer to Develop Vision AI for Breast Radiology

Do you want to contribute to better health for all?

Our research is internationally recognized for the development and evaluation of AI for radiological breast cancer diagnostics with recent publications in Nature, Lancet Digital Health, Radiology, MICCAI, among others. Our group has expertise in radiology, biostatistics and machine learning. We have a strong collaboration with research groups at KTH, and internationally with a group at UC Berkeley.

We are now looking to recruit one research engineer.

Radiology biomarkers as risk factors for future disease

We were recently part of an investigator team awarded funding for the project we call BRISK - Population-based studies of health risks related to breast implants.

Cosmetic surgeries are rapidly rising in prevalence worldwide. Most of these surgeries are performed in private clinics and have therefore not been subjected to registration, reimbursement, nor monitoring of the public health care systems to the same extent as most other medical treatments. Some evidence suggests that women with breast implants have higher risks of various symptoms and medical conditions, recently collectively labelled “breast implant illness” (BII). Large and methodologically sound studies are still needed and, therefore, the overarching aim of the BRISK (Breast Implant Health Risks) project is to significantly advance the current understanding of potentially adverse outcomes of women with cosmetic breast implants and their underlying mechanisms.

Your mission

We are looking for a highly motivated and well-qualified individual to take the responsibility to develop an AI-based image analysis tool in the project to be used to assess breast implants in mammograms. You will be the person responsible for preparing data (mainly radiological DICOM images and linking those to parametric data from registers), collecting annotations from radiologists, and using this to train and test models to predict implant-related parameters such as absolute and relative sizes, complications in the surrounding tissue and implant integrity. You will also be involved in using the output parameters for risk models of various potential diseases to understand whether they contribute to a higher risk or not.

Your profile

 Qualifications

You should have:

• A strong personal interest in developing AI for medical image analysis
• Experience developing AI models for image analysis using recent deep learning architectures and techniques.
• Excellent software engineering skills and great attention to best practices in data science
• Bachelor's or Master's degree in computer science or related field.

It is a merit if you have:

• Experience with developing tools for medical image analysis, especially radiological images.
• Experience with production-grade code, containerization (docker), version control (git), annotation and curation of data, deep learning libraries (such as torch or jax), experiment tracking software (wandb).
• Self-motivation to create a well documented, maintainable and reproducible code-base. Very good communication skills in both writing and speaking, in Swedish.
• Excellent communication skills in both writing and speaking in English.

What do we offer?

A creative and inspiring environment with wide-ranging expertise and interests. Karolinska Institutet is one of the world's leading medical universities. Our vision is to pursue the development of knowledge about life and to promote a better health for all. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. Karolinska Institutet is also a state university, which entitles you to several good benefits through our collective agreement. And you get to practice freely in our modern wellness facilities, where trained staff are on site.

Location: Solna

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Application

Welcome to apply at the latest 12^th January.

The application is to be submitted through the Varbi recruitment system.In this recruitment, you will apply with your CV without a personal letter. Instead, you will answer some questions about why you are applying for the job in the application form. 

This is a fulltime position for approximately 1 year. 

Want to make a difference? Join us and contribute to better health for all