Current openings

To apply for the below positions, please send an email to diag-lab@mun.ca with the subject line [diag-recruitment] Application for <insert the name of the position interested in>. Include a few lines about yourself and attach your CV along with the most recent academic transcript.

PhD positions

We have openings for students interested in pursuing doctoral studies in our lab’s research focus areas. Interested applicants must also follow and successfully complete the formal Computer Science Ph.D. program admission procedures at MUN.

Masters thesis supervision

We are accepting applications from students planning to pursue a thesis based Masters program at MUN. Applicants already accepted into the Computer Science M.Sc. program may directly apply to us indicating interest, whereas students who have yet to obtain admission should also look at the M.Sc. program application instructions, and are expected to successfully complete the M.Sc. program entry requirements.

Undergraduate opportunities

Honors thesis projects

MUN undergraduates in the B.Sc. honors stream are welcome to apply and explore thesis topics to work on with our lab. Topics range from system development (see the full stack software engineering opportunity below) to statistical analysis and machine learning projects involving working with large medical imaging datasets and latest R, MATLAB and Python data science/ML libraries.

USRA/SURA research competitions

We support MUN undergraduates interested in applying to the NSERC Undergraduate Student Research Award (USRA) and Faculty of Science Undergraduate Research Award (SURA) competitions for working on research projects at our lab. Interested applicants should check out the USRA/SURA application procedures and deadlines and get in touch with us.

Full stack software engineering volunteers

We are looking for undergraduates with strong programming skills to join our full stack software development team to support our lab’s research and its real-world translation in the fields of medical image analysis, artificial intelligence (AI) and machine (deep) learning.

The expertise we need right now is in core software development and these projects involve working on one or more aspects of the medical image analysis software production process. Broadly, the software development projects fall under the following four areas: Web design & development, Database systems, Big data processing infrastructure and Medical image manual labeling tools.

Through working on the various projects, you will gain experience in several programming languages (BASH, Python, MATLAB, C/C++, Qt, Ruby/Rails, JavaScript, etc.) & software frameworks (Docker/Singularity, Ansible, OpenStack, SQL, Apache, Spark, etc.), and will also have the opportunity to work with some of the most powerful computing resources available. Further, you will work in a large programming team with members from different parts of the world using source code management tools such as GIT/SVN and following industry-standard best practices like code-reviews and software testing. You will thus gain experience working in a fast-paced, professional software development environment and receive mentorship and guidance in software development and medical image analysis research from senior team members. We strive to provide a supportive team environment, in which you can develop your communication, critical thinking, collaboration and coding skills.

Medical image manual labeling volunteers

We are looking for undergraduates interested in the field of medical image analysis, human anatomy and machine learning to help with the development of cutting-edge automated medical image analysis algorithms that will aid clinicians and researchers better interpret multimodal medical images (CT, MRI etc.), leading to the delivery of improved care to patients. As a contributor to the various manual labeling projects, you will become familiar with analyzing medical images and develop skills in using medical image analysis software. You will gain knowledge about human anatomy and familiarity with computational anatomy and machine learning. This position may provide long term and varied learning experiences as projects in the lab progress during your time here.