KTH Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health
Third-cycle subject: Technology and health
AI-Driven Finite Element Human Body Modelling and Injury Biomechanics for Improved Traffic Safety
This project develops an AI-driven platform to personalize finite element Human Body Models (HBMs) and automatically position them in realistic occupant postures. The project addresses a key challenge in the transition toward HBM-based vehicle safety assessment in consumer ratings and future regulations, where efficient and accurate methods are needed to personalize and position HBMs for industrial deployment. The project also enables systematic reconstruction of real-world accidents from image and video data. On the technical side, the project establishes evidence-based quality criteria for harmonization and robust use across different HBM families, together with data-driven, PCA-based methods. Applicants should have a relevant background in mechanics/computational mechanics/biomechanics, combined with strong programming skills or experience in AI/machine learning. This project is funded by Vinnova under the FFI (Strategic Vehicle Research and Innovation) programme and is carried out in collaboration with Autoliv.
Supervision: Xiaogai Li, Svein Kleiven and Shiyang Meng are proposed to supervise the doctoral student. Decisions are made on admission.
To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:
KTH Royal Institute of Technology is seeking a highly motivated, recently graduated Master of Science in Engineering, with a willingness to travel to research and industry partners.
Preferably, the candidate should have a Master's degree in Mechanical Engineering, Engineering Mechanics, Biomedical Engineering, Engineering Physics or equivalent, with a solid background in mechanics, computational mechanics and/or biomechanics. Strong knowledge of continuum mechanics and the Finite Element Method (FEM), solid programming skills (e.g. Python, Matlab), and experience with AI/machine learning (e.g. deep learning, graph neural networks) are highly meriting.
In addition to the above, there is also a mandatory requirement for English equivalent to English B/6.
In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:
You have ability of working independently, communicating in English and working in group with other researchers. After the qualification requirements, great emphasis will be placed on personal skills.
Only those admitted to postgraduate education may be employed as a doctoral student. The total length of employment may not be longer than what corresponds to full-time doctoral education in four years' time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment may be renewed for a maximum of two years at a time. In the case of studies that are to be completed with a licentiate degree, the total period of employment may not be longer than what corresponds to full-time doctoral education for two years.
As a doctoral student, you are entitled to a workplace with many employee benefits and monthly salary according to KTH's Doctoral student salary agreement. Read more about Doctoral studies (PhD) | KTH | Sweden.
Tagged as: Engineering, Physics
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