Search for University Jobs in Engineering

Job ID: 207900

Doctoral researcher in Machine Learning for Healthcare
Aalto University

Date Posted Mar. 27, 2023
Title Doctoral researcher in Machine Learning for Healthcare
University Aalto University
, Finland
Department T313 Dept. Computer Science
Application Deadline Open until filled
Position Start Date Available immediately
  • Graduate Student
  • Computer Science
Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with nearly 12 000 students and a staff of more than 4000, of which 400 are professors. Our main campus is located in Espoo, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community.

The Department of Computer Science is an internationally-oriented community and home to world-class research in modern computer science, combining research on foundations and innovative applications. With over 40 professors and more than 450 employees from 50 countries, it is the largest department at Aalto University and the largest computer science unit in Finland. Computer science research at Aalto University ranks high in several prominent surveys (47th worldwide and 9th in Europe in Shanghai subject ranking 2019; and 56th worldwide in Times Higher Education subject ranking 2020).

The Department of Computer Science is now looking for a

Doctoral researcher (Ph.D. student) in Machine Learning for Healthcare.

Project description

Deep learning has achieved remarkable performance in various medical classification, regression, and semantic segmentation tasks. However, the current approaches rarely estimate uncertainty in the predictions, which translates to improper level of trust for the models. In this project, the doctoral researcher will contribute to the development and application of uncertainty-aware (e.g., Bayesian), explainable, and controllable deep learning methods for medical data. In the current collaborations we utilize imaging data such as fundus images, CBCT (Cone-Beam Computed Tomography), MRI (Magnetic Resonance Imaging), CT (Computed Tomography), and PET (Positron Emission Tomography). A successful applicant is expected to have a Master’s degree in machine learning or related field, have experience in modern deep learning libraries (e.g., Pytorch or TensorFlow), and have the capacity to develop and apply state-of-the-art models, and to handle real world data.

Your network and team

You will be joining Professor (Emeritus) Kimmo Kaski’s team. The team has the following ongoing interdisciplinary collaborations:
  • Helsinki University Hospital (HUS) and Central Finland Central Hospital for clinical diabetic retinopathy classification using fundus images and additional metadata.
  • Tampere University Hospital (TAUH) and Tampere University (TAU) for various maxillofacial localisation and segmentation tasks from CBCT images.
  • MD Anderson Cancer Center (The University of Texas), HUS and TAUH for various tasks for patients with head and neck cancer or sarcopenia such as treatment planning, surgical planning, and survival analysis from multimodal imaging data (MRI/CT/PET).

Your role and goals

We are looking for a Doctoral Researcher to study uncertainty estimation, explainability, and human-in-the-loop interaction with deep learning models for the healthcare related tasks of our collaborations. Your role will include investigating existing state-of-the-art methods to the novel tasks tackled in the various collaborations, with the possibility of development of novel approaches and methodologies. You will be working on a variety of patient data including 2D and 3D medical imaging as well as tabular data, and with a variety of data modalities, including digital imaging, magnetic resonance imaging, (cone-beam) computed tomography, and positron emission tomography. To facilitate these challenging and interesting research problems, you will be able to utilize high throughput computers with GPUs (Graphics Processing Unit) and secure cluster environments for your research.

Your goal is to produce high quality research, in collaboration with medical experts, to be published in esteemed journals for your doctoral thesis, and to advance the clinical applicability of state-of-the-art algorithms to have a real impact in AI for healthcare.

In addition to research work, people hired are expected to participate in teaching following the standard practices at the department.

Your experience and ambitions

The ideal candidate has the following qualities:
  • Ability to work independently and under pressure.
  • Distinguished study record with related studies in machine learning, computer vision, or statistics. 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.
  • Fluent in English language.
  • Experience with Python and deep learning libraries (e.g., Pytorch or TensorFlow).
  • Team working skills.

If you are chosen for this position, you will apply for the right to study doctoral studies at Aalto University School of Science. Thus, please check the student information and admission criteria Please pay attention to mandatory skill level in English.

What we offer

The position belongs to the Aalto career system and the selected person will be appointed for a two-year fixed term appointment with an option for two-year renewal.

The starting salary for the position is 2 602,14 EUR per month. In addition to the salary, the contract includes occupational health benefits, and Finland has a comprehensive social security system. The annual total workload of research and teaching staff at Aalto University is 1 612 hours. 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 30.04.2023. 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 and visitors should apply for the position via our internal system Workday -> find jobs (not external webpage on open positions) by using their existing Workday user account.

To apply, please share the following application materials with us:
  • Letter of motivation (filename: surname_motivation_letter.pdf)
  • CV (filename: surname_CV.pdf)
  • Transcript of records (filename: surname_transcript.pdf)
  • M.Sc. thesis, and other supporting material (filename: surname_thesis.pdf)
  • List of references and recommendation letters in a single file (filename: surname_recommendations.pdf)

The candidates must have completed their Master’s degree before the start of the contract period. Aalto University reserves the right for justified reasons to leave the position open, to extend the application period, reopen the application process, and to consider candidates who have not submitted applications during the application period.

Further information
  • Professor Kimmo Kaski, e-mail "" (research related information)
  • HR Advisor Maaria Ilanko, e-mail "" (recruitment process)

Want to know more about us and your future colleaguesYou can watch these videos: Aalto University - Towards a better worldAalto People , and Shaping a Sustainable Future. You can also check out our webpage about Aalto and Finland: and check out our new virtual campus experience:

Finland is a great place for living with or without family - it is a safe, politically stable, and well-organized Nordic society. For more information about living in Finland: 

More about Aalto University:

More about Aalto University:

Please reference in your cover letter when
applying for or inquiring about this job announcement.

Contact Information

Please see the job description for contact details
pertaining to this university job announcement.


Refer this job to a friend or colleague!

New Search | Previous

RSS for the latest higher education jobs
Atom for the latest higher education jobs
Need a Sabbatical Home?