Postdoctoral Researcher, Medical Statistics

Academic Positions; Finland; On-site; EUR 44,000 - 47,000; Full time

Job summary

The University of Oulu invites applications for a Postdoctoral Researcher in Medical Statistics within the Population Health Research Unit (PoPH) in the Faculty of Medicine. The role focuses on longitudinal models of chronic diseases and data‑driven machine learning using real‑world health data.

The successful candidate will design reproducible studies, develop ML approaches for cohort data, and contribute to scientific publications and grant proposals.

Qualifications

• Doctoral degree in health data science, bioinformatics, statistics, computer science or related; completed by end of the application period and within 10 years prior.
• Experience using, evaluating and developing machine learning methods with strong analytical and programming skills (R or Python)
• Experience with accurate, reproducible data preparation and analysis
• Track record of peer‑reviewed research articles, research software and/or datasets
• Ability to organise competing priorities and deliver high-quality work on deadlines
• Ability to work independently and take responsibility for planning and delivering tasks
• Collaborative and inclusive approach to interdisciplinary teamwork
• Excellent written and spoken English
• Familiarity with Finnish language is appreciated

Responsibilities

• Extract, link, clean and manage data from health sources
• Design reproducible studies and evaluate models
• Build and evaluate longitudinal models and research software
• Write scientific articles and contribute to team-led publications
• Present findings in scientific meetings at unit, university and external venues
• Contribute to documentation, project reporting and funding applications

Skills

Machine learning methods

Programming (R or Python)

Data preparation

Analytical thinking

English (written and spoken)

Independent work

Team collaboration

Documentation and reporting

Education

Doctoral degree in related field

Job description

Organisation/Company University of Oulu Research Field Biological sciences › Other Computer science › Other Mathematics › Statistics Medical sciences › Other Researcher Profile Recognised Researcher (R2) Application Deadline 4 Oct 2026 - 20:59 (UTC) Country Finland Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The University of Oulu is a multidisciplinary, international research university, with about 4000 employees who produce new knowledge based on high-standards research and provide research based education to build a more sustainable, smarter, and more humane world. The University of Oulu community has about 19,000 people in total. Our northern scientific community operates globally and creates conditions for the emergence of innovations. The University of Oulu is ranked in the top 3% of the world’s universities. All our research, education, and community activities are guided by our university’s values and ethical principles.

We are inviting applications for a

Postdoctoral Researcher in Medical Statistics

to join us in the Research Unit for Population Health (PoPH), a multidisciplinary research and teaching unit in the Faculty of Medicine. The position is set within Health Dimensions, a multidisciplinary research initiative funded by the Research Council of Finland. Health Dimensions explores the complex, multidimensional nature of human health, with the aim to prevent chronic diseases and multimorbidity through a new level of understanding and acting on these dimensions - lifelong molecular, physiological, environmental, behavioural and societal mechanisms.

About the job

The successful candidate will join a research group working on longitudinal models of multiple chronic diseases across the life course. The postdoctoral researcher will contribute to building and evaluating machine learning models for multiple chronic diseases in real-world data and cohort studies. To successfully work in this position, experience of data-driven analytical approaches, machine learning and advanced longitudinal modelling utilising real-world health and healthcare data is essential.

Key responsibilities

• Extract, link, clean and manage data from administrative health and healthcare data and other relevant sources
• Design reproducible studies and evaluate models using appropriate analytical methods
• Build and evaluate reproducible longitudinal models and research software
• Write scientific articles and contribute to articles led by other members of a multidisciplinary team
• Present research findings in scientific meetings at the unit, university and externally
• Contribute to information governance documentation, project reporting, stakeholder meetings and funding applications

Who are you?

You will need the following

• A doctoral degree in health data science, bioinformatics, statistics, computer science or a closely related discipline. Your doctoral degree should be completed by the end of the application period and no longer than 10 years prior.
• Experience of utilising, evaluating and developing machine learning methods, with strong analytical and programming skills (e.g. R or Python)
• Experience of undertaking accurate, reproducible data preparation and analysis
• A track record of peer-reviewed research articles, research software and/or datasets
• Ability to organise competing priorities and deliver accurate, high-quality work to an agreed timetable
• Ability to work independently and take responsibility for planning and delivering tasks
• A collaborative and inclusive approach to interdisciplinary teamwork
• Excellent written and spoken English

We will also appreciate

• Excellent written and spoken Finnish
• Familiarity with research computing, virtual server solutions and software development
• Ability to communicate technical or clinical research concepts clearly to academic and non-academic audiences

What we offer

• The support of a highly experienced and enthusiastic research team and unit, with whom you can share and develop your expertise
• Career development and learning opportunities in a multidisciplinary, international university setting and within Health Dimensions research initiative
• University of Oulu has an HR Excellence in Research -quality label, which is a recognition awarded by the European Commission for the development of researchers’ working conditions and careers.
• Finland is one of the most livable countries in the world, with a high quality of life, safety, an excellent education system, and a competitive economy. Read more about living in Oulu .

Contract and salary

This is a fixed-term position, with an anticipated starting date of 1st November 2026 (or as soon as possible thereafter) and an expected end date of 31st August 2028.

The salary will be based on the levels 5-6 of the demand level chart for teaching and research staff at Finnish universities. In addition, a salary component based on personal work performance will be paid (a maximum of 50 % of the job-specific component). The starting gross salary will be approx. 3900-4200 € per calendar month.

A trial period of 6 months is applied to the position.

We welcome applicants from all backgrounds, such as people of different ages, genders, and linguistic, cultural and ethnic groups.University of Oulu is committed to supporting and promoting equality and diversity and to creating an inclusive environment for all.

Contact Information

For questions, please contact Associate Professor Katriina Heikkila (katriina.heikkila[at]oulu.fi).

Please do not send any application documents to this email address.

Text edited 28.9.2026: application deadline changed from 30.9.2026 to 4.10.2026.

Type of employment: Temporary position
Contract type: Full time
Number of positions: 1
Full-time equivalent: 100%
City: Oulu
County: Pohjois-Pohjanmaa
Country: Finland
Reference number: 2026/576
Published: 2026-09-18
Last application date: 2026-10-04