Master’s thesis position (M.Sc. student) in Deep Learning for Healthcare

The Department of Computer Science is now looking for a

Master’s thesis position (M.Sc. student) in Deep Learning for Healthcare.

Project description:

Deep learning has achieved remarkable performance in tasks in the field of healthcare including medical image analysis based on detection, classification, or segmentation. However, the current approaches lack explainability resulting in reduced trust in these methods. Moreover, deep learning techniques often require a large amount of labelled data which can be difficult to obtain in the healthcare domain. Thus, techniques improving data efficiency can be integral for healthcare applications. The master’s thesis worker will be collaborating in one of the medical imaging use cases being researched in the “MEDALLION: Medical AI and Immersion” project (read more: https://medallion-project.info):

• Pancreatic cystic lesion analysis​
• Intracranial brain aneurysm analysis​
• Postmortem identification and bone quality analysis

The precise topic for the thesis will be discussed and agreed on later.

Your role and goals

In one of these topics, the master’s student will be developing deep learning -based detection, classification and/or segmentation methods that use clinical volumetric imaging data (e.g., MRI, CTA, CBCT) including medical expert annotations. Moreover, the analysis could be extended with weak supervision, semi-supervision, self-supervision, or explainability techniques such as uncertainty-aware deep learning or Grad-CAM.

Your network and team

You will be working with researchers and students in the Digital Health, Wellbeing and Resilience research group led by Professor Kimmo Kaski. Through the MEDALLION project you will be collaborating with academic researchers from Tampere University, medical professionals from Tampere University Hospital, and industrial collaborators. More information about our research group can be found from: https://www.aalto.fi/en/department-of-computer-science/digital-health-wellbeing-and-resilience

Your experience and ambitions

The ideal candidate has the following qualities:

• Distinguished study record with related studies in deep learning and computer            vision. Satisfactory skill in mathematics is required. Studies including medical imaging and health-related topics are seen as an advantage.
• Ability to design and carry out machine learning experiments in a careful and systematic manner.
• Ability to work both independently and in a team.
• Fluent in the English language.
• Experience with Python and PyTorch. In addition, experience with semi-, self- or weakly supervised training techniques or explainability techniques (e.g., uncertainty-aware deep learning, Grad-CAM) are seen as an advantage.

What we offer

The position is a fixed term of 6 months. The salary for the position is 2 564,18 EUR per month. In addition to the salary, the contract includes occupational health benefits, and Finland has a comprehensive social security system. Daily working time for full-time employees is 36 hours 15 minutes weekly. The position is located at the Aalto University Otaniemi campus.

Ready to apply?

If you want to join our community, please submit your application through our online recruitment system by using the link on Aalto University’s web page ("Apply now”).

The deadline for applications is 15.1.2026. Please submit your application promptly. The position will be filled as soon as a suitable candidate has been identified.

Please note: Aalto University’s employees should apply for the position via our internal HR system Workday (Internal Jobs) by using their existing Workday user account (not via the external webpage for open positions). Aalto University’s students and visitors should apply as external candidates with personal (not Aalto) email.

To apply, please share the following application materials with us:

• Letter of motivation
• CV
• Transcript of records
• Other supporting material

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