Jobid=964c1ebe07f8 (0.0169)
ph3EngD position: Design tool for tire-snow performance predictions /h3pLooking for a job that matters? Join the university of technology that puts people first – and shape new opportunities both for yourself and for ou… /ppWinter tires are characterized by excellent performance at cold temperatures and in snowy conditions. The development of new winter tires, however, can be challenging. For example, mold production is time consuming (due to all the small details – the so-called sipes – that are required for snow grip) and the quality and behavior of snow is highly variable, which is a challenge for design when comparing outdoor test results with laboratory conditions. Therefore, numerical simulation tools are being developed to better estimate the effect of design changes on the tire performances – especially relevant at the early stages of the development of new tires. /ppApproach /ppAlthough numerical simulation environments have been developed to predict the snow performance of newly developed tire prototypes, challenges remain in comparing and validating advanced numerical models, e.g., using the Arbitrary Lagrangian-Eulerian (ALE), Coupled Eulerian-Lagrangian (CEL), and Smoothed particle hydrodynamics (SPH) methods for snowy conditions. Furthermore, investigation on the speed, accuracy, and convergence of these models and integration within the simulation environment of Apollo is required to ensure the robustness of the tire prototyping process. /ppFinal goal /ppThe project aims to develop a comprehensive numerical model for tire-snow interaction: coupled numerical models for rubber-snow interaction will be implemented using the Abaqus software. The main objective is to select the most suitable solution, from the perspective of stakeholder demands, and implement and integrate it into Apollo’s professional environment. The accuracy for predicting snow performance of winter tires will be validated experimentally, followed by further model improvements, and implementation or design of a robust workflow and predictive design tool. /ph3Your profile /h3pRequirements (hard-skills): /pulliMSc graduate in Mechanical Engineering, Physics, Civil Engineering, or related fields /liliKnowledge of Finite Element Method (FEM) /li /ulpNumerical simulation (e.g. Abaqus, UMAT) and coding experiences (Python, Fortran) are a must /ph3Our offer /h3pWe offer a position in an inspiring, multidisciplinary and international environment with an attractive campus and lots of facilities for sports and leisure. /ppThe university provides a dynamic ecosystem with enthusiastic colleagues. /ppExcellent facilities for professional and personal development /ph3Are you interested in being part of our team? /h3pPlease send your application by b30th April 2026 /b, via the “apply now” button and include: /pullicontact details of at least 2 references. /li /ulpInterviews are planned for the last two weeks of May.br/Screening is part of the procedure. /ph3About the organisation /h3pThe Faculty of Engineering Technology (ET) engages in education and research of Mechanical Engineering, Civil Engineering and Industrial Design Engineering. We enable society and industry to innovate and create value using efficient, solid and sustainable technology. We are part of a ‘people-first’ university of technology, taking our place as an internationally leading center for smart production, processes and devices in five domains: Health Technology, Maintenance, Smart Regions, Smart Industry and Sustainable Resources. Our faculty is home to about 2,900 Bachelor’s and Master’s students, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutesMesa+ Institute, TechMed Center and Digital Society Institute. /ph3Job details /h3pTitle /ppEngD position: Design tool for tire-snow performance predictions /ppPublished /p /p #J-18808-Ljbffr
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