DC 11 – Participatory modelling the societal complexity of use of in silico models to design uptake strategies

1. Overview of the research programme:

InSilicoHealth is an innovative Doctoral Network (DN) with the ambition to train a new generation of outstanding
Doctoral Candidates (DC) that will become effective translators of the rapidly evolving digital technology to tackle
existing and future challenges related with healthy ageing in Europe. The research focus of this DN lies in three
key domains: the brain, heart, and musculoskeletal (MSK) systems. In the realm of digital technology, InSilicoHealth
specifically focuses on virtual human twin (VHT) technology to enhance our understanding of the age-related adaptive
changes of the complex human body through predictive multi-scale simulations. The research methodology employs
knowledge-driven models enhanced by advanced data-driven inference techniques to optimize the health potential of
older individuals.

2. Individual PhD Project Information:

Host institution:

KTH Royal Institute of Technology (KTH), Sweden

Supervisory team:

Prof. Sebastiaan Meijer (PhD supervisor, KTH), Dr Michiel Van Oudheusden (PhD co-supervisor, VU Amsterdam),
Prof. Paolo Parini (secondment host, Karolinska University Hospital).

Enrolment in Doctoral School:

Enrolled in the School of Chemistry, Biotechnology and Health program of Technology and Health (KTH) and the
Athena Graduate School (VU Amsterdam).

PhD project description:

3. PhD project description:

This PhD project will focus on developing and deploying a participatory modelling research protocol that captures the
agency complexities, incentive structures and structural hindrances at a descriptive structural level. The
objectives are: 1) Select and onboard relevant real-world stakeholders to participate in the model building; 2)
Deploy a series of model building and validation sessions to obtain a validated model; 3) Develop an actionable
policy intervention using the systems dynamics model to inform policy formulation for in silico health; 4) Evaluate
the value of the approach for furthering the in silico health uptake in real-world health care.

A successful project will provide insights into the actor and agency complexity of in silico model deployment from
the development and validations of a system dynamics model, and actionable participatory methods to develop uptake
policies at the hospital level, developed with relevant stakeholders and validated against the other DCs.

4. Planned secondments:

VU Amsterdam : deep dive into social and institutional dynamics in health care organisations.

Karolinska University hospital : Opportunity to be embedded in real-world use contexts of in silico models
allows for participatory modelling in place. These include clinical and management levels at the hospital, as
well as the regulatory bodies at the regional level as owners of the hospital system.

5. Essential requirements:

You have completed a master’s degree in modelling and simulation methods in sociotechnical systems or health
sciences, or possess corresponding qualifications that could provide a basis for successfully completing a
doctorate.

You have proven your proficiency in English language equivalent to B2 level.

You did not reside or carry out your main activity (work, studies, etc.) in Sweden for more than 12 months in
the three years before 1st of January 2025.

You are ambitious, well organized, a team player, and have excellent communication skills.

You can work independently and have a critical mindset.

You are a pro-active and motivated person, eager to participate in network-wide training events, international
mobility, and public dissemination activities.

Previous experience in construction of systems dynamics models, dynamic model assessment with network
algorithms, and/or multi-level model validation is not required but considered a plus.