Postdoc position: Computational Biomechanics for Fall Protection

• Develop and validate finite element models using LS-DYNA, OpenRadioss, or equivalent solvers to simulate skull fracture mechanics during impact scenarios
• Perform parametric studies for population-level analysis
• Develop protocols for various fall scenarios and demographic parameters

• Design and execute experimental protocols for material property characterization of protective materials
• Perform validation studies to ensure computational model accuracy against experimental benchmarks
• Collaborate on the development of testing methodologies for protective device evaluation

• Develop and implement machine learning algorithms to enhance the design optimization process
• Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations
• Integrate ML approaches with finite element simulations to create intelligent design tools

• Work closely with startup partners to ensure research alignment with commercial objectives
• Participate in regular progress meetings and technical discussions with industry collaborators
• Contribute to the development and maintenance of open-source libraries

• Ph.D. in Mechanical Engineering, Biomedical Engineering, Applied Mechanics, or a closely related field (awarded no more than three years prior to the application deadline)*
• Strong background in computational mechanics and numerical methods
• Demonstrated experience with LS-DYNA or comparable commercial FEA software
• Proficiency in Python programming for scientific computing and machine learning applications
• Experience with machine learning methods and frameworks (scikit-learn, PyMC, or similar)
• Previous experience collaborating with external partners, industry, or commercial entities

• Experience in biomechanics, particularly head/skull injury mechanics or impact biomechanics
• Knowledge of material characterization techniques and experimental mechanics
• Familiarity with optimization algorithms and design of experiments methodologies
• Experience with high-performance computing environments
• Track record of publications in peer-reviewed journals
• Previous experience with Open Science practices (e.g. contributions to open-source libraries, research data repositories)

• Strong communication skills for interdisciplinary collaboration
• Ability to work independently while maintaining productive team relationships
• Interest in translational research with real-world applications
• Adaptability to work in both academic and industry-oriented environments

• As a postdoc at Chalmers, you are an employee and enjoy all employee benefits. Read more about

• A dynamic and inspiring working environment in the coastal city of

• Read more about Sweden's generous parental leave, subsidized day care, free schools, healthcare etc at

• A comprehensive CV, including a complete list of publications.

• Details of previous teaching and pedagogical experience.

• A brief introduction about yourself.

• A summary of your previous research fields and key research outcomes.

• An outline of your future goals and research focus.

Chalmers tekniska högskola