Summary
KTH Royal Institute of Technology invites applications for a fully funded Doctoral (PhD) position in Neuronics at the School of Engineering Sciences in Chemistry, Biotechnology and Health. The project, funded by Vinnova under the FFI programme in collaboration with Autoliv, focuses on developing an AI-driven platform to personalize finite element Human Body Models (HBMs) and automatically position them in realistic occupant postures for improved vehicle traffic safety and real-world accident reconstruction.
Doctoral Position in Neuronics: AI-Driven Finite Element Human Body Modelling and Injury Biomechanics
Designation
Doctoral Student / PhD Candidate (Third-cycle subject: Technology and Health)
Position Overview
| Parameter | Details |
| Institution | KTH Royal Institute of Technology |
| School/Department | School of Engineering Sciences in Chemistry, Biotechnology and Health |
| Target Degree | Doctoral Degree (PhD) |
| Position Type | Temporary (Full-time, up to 4 years) |
| Salary | Monthly salary according to KTH’s doctoral student agreement |
| Reference Number | PA-2026-2847 |
| Collaboration Partner | Autoliv (Funded by Vinnova / FFI programme) |
| Supervisors | Xiaogai Li, Svein Kleiven, and Shiyang Meng |
| Application Deadline | October 1, 2026 (Midnight CET/CEST) |
Research Area
- Field: Technology and Health / Biomechanics
- Specific Topics:
- AI-Driven Finite Element (FE) Human Body Modelling (HBM)
- Injury Biomechanics & Traffic Safety Assessment
- Data-driven, Principal Component Analysis (PCA)-based morphing methods
- Automated vehicle occupant positioning and accident reconstruction from image/video data
Location
Stockholm, Sweden (KTH Royal Institute of Technology)
Eligibility & Qualifications
Basic Admission Requirements
- Completed a second-cycle degree (e.g., Master’s degree), or
- Completed at least 240 higher education credits (with at least 60 credits at the second-cycle level), or
- Acquired substantially equivalent knowledge within or outside Sweden.
- Mandatory English proficiency equivalent to the Swedish upper secondary course English B / English 6.
Specific Qualifications & Merit
- Master of Science degree in Mechanical Engineering, Engineering Mechanics, Biomedical Engineering, Engineering Physics, or an equivalent discipline.
- Solid background in continuum mechanics, computational mechanics, or biomechanics.
- Experience with the Finite Element Method (FEM).
- Strong programming skills (e.g., Python, MATLAB).
- High merit: Background in AI / Machine Learning (such as deep learning, graph neural networks).
- Willingness to collaborate and travel to research/industry partners.
Scholarship / Employment Description
- The position is a fully funded doctoral employment for up to four years of full-time doctoral education.
- Initial employment is for one year, renewable for up to two years at a time.
- Doctoral students are standard employees entitled to statutory employee benefits, social security, pension contributions, and a competitive monthly salary structured by KTH’s collective agreement.
- Up to 20% of the working time may include departmental tasks such as teaching and administration.
How to Apply
Applications must be submitted electronically through the KTH Recruitment Portal before the deadline.
Required Application Documents:
- Curriculum Vitae (CV): Detail your education, relevant professional experience, and technical skill set.
- Application Letter (Cover Letter): Maximum 2 pages explaining why you want to pursue research studies, your academic interests, and how your previous experience aligns with the project goals.
- Certified Copies of Degrees & Transcripts: Diplomas and official grade records from previous university education (with certified English or Swedish translations if original is in another language).
- Language Certificate: Proof of English proficiency.
(Note: Do not attach large publication files or extended reports unless specifically requested).
Last Date for Apply
October 1, 2026 at 23:59 (Midnight CET / CEST).
