The Western Norway University of Applied Sciences (HVL) invites applications for a PhD position linked to the 'Bump2Baby & Me+' project, focusing on artificial intelligence for personalised digital health interventions targeting women at risk of gestational diabetes mellitus (GDM). HVL is one of Norway’s largest higher education institutions, offering a broad range of academic programmes across five campuses. The Faculty of Health and Social Sciences, with around 4,900 students, provides diverse programs in health and social care, including several master’s and PhD programs.

This PhD position is based in the Department of Health and Caring Sciences, Section of Specialist Nursing, and is anchored in the Bump2Baby & Me+ research project. The project aims to implement health-promoting interventions for women at increased risk of GDM, leveraging artificial intelligence to evaluate and inform digital health strategies. The research will primarily utilize data from a completed randomized controlled trial, combining advanced machine learning techniques with qualitative methods to investigate health app usage patterns and engagement across multiple European countries. The ultimate goal is to identify factors that improve health outcomes for mothers and children and to strengthen the implementation of digital health interventions in clinical practice.

The successful candidate will join the DiaBEST research group, which focuses on the psychosocial aspects of living with diabetes and other chronic diseases. The position is funded by the Faculty of Health and Social Sciences at HVL and is part of a four-year PhD program, with 25% of the time dedicated to career-enhancing activities. The candidate will be enrolled in the interdisciplinary PhD program Responsible Innovation and Regional Development (RESINNREG), which examines how innovation can address social, economic, and environmental challenges in regional contexts.

Applicants must hold a relevant master’s degree (120 ECTS) with qualifications in digital health, data analysis, and/or machine learning applied to health research. The master’s thesis (minimum 30 ECTS) must be submitted by the application deadline, and the degree approved within four weeks after the deadline. A minimum grade of B for the thesis and an overall average grade of C for other courses is required. Preferred qualifications include experience in responsible innovation, health intervention implementation, digital health, data analysis, machine learning, research methodology, statistics, scientific publications, pregnancy and women’s health research, international research, programming (R, Python), PCA and cluster analysis, and proficiency in English, Norwegian, or another Scandinavian language. Personal qualities such as analytical thinking, independence, collaboration skills, motivation, perseverance, and high ethical awareness are essential.

The position offers attractive pension, insurance, and loan schemes through the Norwegian Public Service Pension Fund, with salary progression according to seniority. The PhD stipend is paid according to position code 1017, and a 2% contribution to the pension fund is deducted from the salary. HVL provides an exciting academic environment with opportunities for professional development and exercise during work hours.

To apply, submit your application and CV via the 'Apply for this position' button on the jobbnorge.no page. Ensure all relevant attachments are uploaded, including your master’s thesis, up to five scientific works, publication list, certificates, and transcripts. Certified translations must be provided for documents not in English or a Scandinavian language. Applications are assessed based on information submitted by the deadline. Applicants with foreign education must document equivalence to a Norwegian degree. Shortlisted candidates will be invited for an interview and trial lecture. The position is available as soon as possible, and no later than 15 August 2026. For further information, contact Assistant head of department Marianne Fjose or Associate professor Hilde Kristin Refvik Riise.