Arbetsbeskrivning

Join a research team developing state-of-the-art open-source computational tools in a project that aims to create life-saving technology to prevent devastating skull fractures in elderly populations. This unique position combines advanced finite element modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an innovative startup partner. You will be at the forefront of translating computational research into real-world protective devices that can make a meaningful impact on public health. Project overview This position is part of an interdisciplinary research initiative focused on developing computational tools for designing protective devices to prevent skull fractures in elderly falls. The project leverages finite element modeling as the foundation of a comprehensive design framework that integrates simulation, experimentation, and machine learning. Fall-related injuries are a leading cause of morbidity and mortality in aging populations, making this work a critical public health priority. The successful candidate will work in a collaborative environment that bridges academic research and industry application, thanks to our partnership with a dynamic startup company. This collaboration provides unique opportunities for technology transfer, commercialization, and exposure to the entrepreneurial aspects of research translation. The Division of Vehicle Safety The Division of Vehicle Safety studies accidents, driver reactions, and injury mechanisms. The Injury Prevention group develops Human Body Models to predict injuries for the whole population, in collaboration with industry, academia, authorities, and insurance companies. Main responsibilities Computational Modeling and Simulation • 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 Experimental Validation and Material Characterization • 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 Machine Learning Integration • 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 Industry Collaboration and Utilization • 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 Required qualifications • 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 Preferred qualifications • 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) Personal attributes • 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 *The date on your doctoral degree certificate is considered the official date of completion. Exceptions to the three-year eligibility limit may be made for documented circumstances such as parental leave, sick leave, or military service.  Contract terms The position is a temporary full-time employment for two years with the possibility of a one-year extension.  The position requires physical presence throughout the entire employment. A valid residence permit must be presented by the start date, otherwise the offer may be withdrawn.  What we offer  • As a postdoc at Chalmers, you are an employee and enjoy all employee benefits. Read more about working at Chalmers and our benefits for employees.  • A dynamic and inspiring working environment in the coastal city of Gothenburg.  • Read more about Sweden’s generous parental leave, subsidized day care, free schools, healthcare etc at Move To Gothenburg.  Chalmers is dedicated to improving gender balance and actively works with equality projects, such as the GENIE Initiative for gender equality and excellence.  If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in.  How to apply  The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.  CV  • A comprehensive CV, including a complete list of publications.  • Details of previous teaching and pedagogical experience.  Personal letter  • 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.  Use the button at the foot of the page to reach the application form.     Application deadline: 30 September, 2025