PhD on ML accelerated simulations and uncertainty quantification of composites
Job Summary
We are hiring for a PhD candidate in the area of multiscale and multiphysics modelling of sustainable fibrous composites, focusing on uncertainty quantification and machine learning. Natural fiber reinforced composites are used in fields like construction, automotive, and consumer products, but they face challenges due to moisture-induced degradation and variability in properties.
Responsibilities
- Develop numerical models for coupled mechanical-diffusive-thermal-chemical behavior of fiber-reinforced composites at micro/meso-scale, incorporating uncertainty via stochastic inputs.
- Analyze responses using techniques such as Monte Carlo simulations.
- Identify variability of model parameters using Bayesian inference.
- Quantify impact of microscale uncertainties on macroscale performance through stochastic homogenization and uncertainty propagation methods.
- Integrate machine learning techniques to accelerate simulations and enable faster predictions while preserving uncertainty information.
Qualifications and Requirements
- Talented, motivated, and enthusiastic researcher with analytical skills, initiative, and creativity.
- MSc degree in Mechanical Engineering, Civil Engineering, Computational Mechanics, Mathematical Engineering, or equivalent.
- Strong background in mechanics of materials and multi-scale and multi-physics methods.
- Additional expertise in uncertainty quantification and/or machine learning techniques is advantageous.
- Interest in interdisciplinary projects with significant social and industrial impact.
- Excellent oral and writing skills in English at C1 level.
What the Employer Offers
- Fixed-term contract for 4 years.
- Full-time employment with a minimum of 10% and maximum of 15% per year on teaching tasks.
- Salary between €3,059 and €3,881 per month, in accordance with the Collective Labour Agreement for Dutch Universities, scale P.
- Benefits including pension scheme, paid pregnancy and maternity leave, partially paid parental leave, year-end bonus of 8.3%, and annual vacation pay of 8%.
- High-quality training programs, excellent technical infrastructure, on-campus children's day care, sports facilities, allowance for commuting, working from home, and internet costs.
- Staff Immigration Team and tax compensation scheme for international candidates.
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