Development of mechanistic finite element models for structural analysis and machine learning methodologies focused on the inference of surrogate (reduced) models. Integration of these models in a digital twin that recommends optimal operational strategies for structural health maintenance.
Division/Group: Materials and Manufacturing division, Design and Mechanical Assessment group
Industrial, mechanical, mathematical engineer or similar with Master’s degree
Date of degree: 2020 or later (excluding Final Project).
Software: Matlab, Abaqus
Others: Experience in Machine Learning, programming (Python, Matlab, Fortran) and finite element software.
Join a leading technology research company with a clear mission to serve society. Enjoy the opportunity to grow and develop professionally in a positive working environment built on teamwork and trust. Thesis should be completed in 3 years, but may be extended to 4.
Start date: Immediate
- winter: 7 hours, 45 minutes a day. July and August: 6 hours a day (without a lunch break).
- Flexitime, starting between 8:00 and 9:30, earliest departure from 16:15.
- Candidates may choose to leave early on Fridays by working through lunch hour.
Vacation: 23 days + Christmas holiday (24 Dec–2 Jan).
Send the following documentation by email to firstname.lastname@example.org
- Cover letter
- Current CV with photograph
- Academic Transcript