EngD position: Design tool tire-snow predictions

EngD position:
Design tool for tire-snow performance predictions

Looking for a job that matters? Join the university of technology that puts people first – and shape new opportunities both for yourself and for ou...

Winter 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.

Approach

Although 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.

Final goal

The 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.

Requirements (hard-skills):

• MSc graduate in Mechanical Engineering, Physics, Civil Engineering, or related fields
• Knowledge of Finite Element Method (FEM)

Numerical simulation (e.g. Abaqus, UMAT) and coding experiences (Python, Fortran) are a must

We offer a position in an inspiring, multidisciplinary and international environment with an attractive campus and lots of facilities for sports and leisure.

The university provides a dynamic ecosystem with enthusiastic colleagues.

Excellent facilities for professional and personal development

Please send your application by 30th April 2026
, via the "apply now" button and include:

• contact details of at least 2 references.

Interviews are planned for the last two weeks of May.
Screening is part of the procedure.

The 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 institutes

Mesa+ Institute, Tech Med Center and Digital Society Institute.

Title

EngD position:
Design tool for tire-snow performance predictions

Published