ADDITIONAL ESSENTIAL REQUIREMENTS: Master Degree in Engineering with a background in mechanical engineering, electrical engineering, computer science, AI, or related field, with outstanding study results.DESIRABLE REQUIREMENTS:
1. Programming experience in Python, particular experience in common deep learning frameworks (e.g., PyTorch and TensorFlow) would be a benefit;
2. The qualities to carry out independent research, demonstrated e.g., by the grades obtained in your (under)graduate program(s);
3. Is comfortable assisting in data collection experiments with participants in general but older ones in particular;
4. A critical mindset.
SELECTION CRITERIAAll eligible applications will be assessed by a Selection panel according to the following criterion “Qualifications and previous experience” and related sub-criteria:Selection criterion and sub-criteria for admission to the shortlist - ScoreQualifications and previous experience - 0-50,0A. quality of academic performance - 12,5B. current knowledge and expertise - 12,5C. relevant research skills - 12,5D. motivation to apply - 12,5Selection criterion and sub-criteria of shortlisted candidates - Maximum ScoreCommunication and Personal skills - 0-70,0E. Ability to design and conduct original research in the subject area of the individual research project - 15F. Excellent oral communication in English - 11G. Enthusiasm, proactivity, creativity and commitment - 11H. Interpersonal skills - 11I. Attitude to team working and in working in local and international setting - 11J. Expected impact of the doctorate on the DC’s future career - 11OBJECTIVESOverall objective: To develop, test, validate, and valorise decolonized, just and trustworthy FMs and an FMs-based application for assessing FOG severity in the clinic and everyday life (the FOG severity assessment will be one use case to test and validate the Framework).Specific research objectives:
5. Analyse the technical gaps and obstacles that hinder the implementation of social justice in AI systems in healthcare for FOG; identify technical requirements for the development of just FMs-based solutions for FOG.
6. Develop a data collection method embedding wearable IMU sensors for monitoring FOG in everyday life and providing FOG severity assessment; curate a database of large-scale multi-label gait datasets; develop FMs that can be pretrained based on the curated database, fine-tuned to assess FOG severity, and include semi-automatic bias detection and mitigation.
7. Develop an application for FMs-based enhanced FOG severity assessment in the clinic and everyday life; test and validate the FMs-based application for FOG severity assessment through a pilot action in an every-day life use setting.
8. According to the technical perspective, investigate the transferability of the FM-based application for FOG to other clinically relevant gait assessment use-cases; provide insights for standardisation from the technical/engineering perspective.
EXPECTED RESULTS:
9. Meticulously curated multi-label datasets for the development of gait assessment FMs;
10. A FM for assessing FOG severity;
11. A FMs-based application for FOG severity assessment.
INDICATIVE PLANNED SECONDMENTS
12. Radboud University Medical Center (Nijmegen, Netherlands)
13. Emory University (Atlanta, USA)
Further analysis might be required, based on the development of research project.MAIN SUPERVISOR: Prof. Bart Vanrumste (e-mail: bart.vanrumste@kuleuven.be)Due to the high transdisciplinarity of the project, the main supervisor will collaborate with other (co-)supervisors from other project’s partners.HIRING INSTITUTION: KU Leuven (Belgium) PHD ENROLLMENT: The doctoral candidate will be enrolled at the Arenberg Doctoral School of KU Leuven (Belgium) DOCTORAL SCHOOL AND RESEARCH TEAM The PhD researcher will be part of the eMedia research lab under the supervision of Prof. Bart Vanrumste. The research group is embedded in the Department of Electrical Engineering (ESAT) of KU Leuven. Prof. Vanrumste’s research focuses on multimodal sensor integration and machine learning for monitoring of older persons and patients with chronic diseases.
Duration of the employment: 48 months since 1st September 2026 (expected date of the recruitment)
Income: 4.010,00 € Gross per month (48.120,00€ / year).
Benefits:
710 € Mobility Allowance per month (8.520€ / year)
660 € Family Allowance per month (7.920€ / year) - Applicable only when the recruited doctoral candidate has family obligations according to the Marie Skłodowska-Curie rules, i.e., when the recruited Doctoral candidate has persons linked to him/her by:
14. marriage, or
15. a relationship with equivalent status to a marriage recognised by the legislation of the country or region where this relationship was formalised; or
16. dependent children who are actually being maintained by the doctoral candidate
Benefits are gross EU contribution to the salary cost of the doctoral candidate. The net salary will result from deducting all compulsory (employer/employee) national social security contributions as well as direct taxes.
HOW TO APPLY
Applications must be sent exclusively in English and through the online application system cross-referenced in this vacancy. Applications sent through other means or in other languages (other than English) will not be evaluated.
Candidates are required to submit the following documents:
17. a complete CV in Europass Format in English that must highlight activities and place where the activities have been carried out in order to give evidence of fulfilling the mobility eligibility criterion (see above). Use the template available at https://europass.cedefop.europa.eu/it/documents/curriculum-vitae/templates- instructions;
18. a complete academic CV in English with references to past research and training experiences;
19. a motivation letter, in English, highlighting the consistency between the candidate‘s profile and the chosen DC position for which he/she is applying;
20. at least 2 letters of Academic reference, in English or in certified translation;
21. scan of the degree qualification, with certified translation in English (if the degree qualification is not in English);
22. proof of language proficiency;
23. scanned copy of valid identification document (identity card or passport);
24. Declaration of Honour according to the template available on the website https://justhealth-project.eu/ for download;
25. (OPTIONAL) Any further and relevant supporting documents (e.g., research publications, document attesting proficiency in another language).