PhD in AI-Driven Battery Degradation Modeling

Siemens Digital Industries Software; Vlaams-Brabant; On-site; EUR 62,000 - 76,000; Full time

Benefits offered by this job

Mobility allowance

Family allowance

Salary according to MSCA

Job summary

Siemens Industry Software NV in Leuven invites applications for a PhD position to develop a Digital Twin for predictive ultra-fast charging within TRAIN-FAST networks. The project is in collaboration with POLITO and offers cross-disciplinary training in ML, MOR, and multi-physics modelling.

You will work in a multi-institution environment, contribute to publications and secondments, and be enrolled in a POLITO PhD program. The role emphasizes industrial relevance and scientific excellence.

Qualifications

• Two-year master’s degree or equivalent level required.
• Experience with numerical modelling is advantageous.
• Strong English communication skills are essential.

Responsibilities

• Develop a multi-scale, multi-physics workflow for battery degradation.
• Combine ML and Model Order Reduction to approximate PDEs in high-dimensional spaces.
• Collaborate with TRAIN-FAST network and industrial partners.
• Publish findings and present at conferences.

Skills

Numerical modelling

Machine Learning

Multi-physics modelling

English communication

Education

Two-year master’s degree or equivalent

Job description

Siemens Industry Software NV in Leuven invites applications for a PhD position to develop a Digital Twin for predictive ultra-fast charging within TRAIN-FAST networks. The project is in collaboration with POLITO and offers cross-disciplinary training in ML, MOR, and multi-physics modelling.

You will work in a multi-institution environment, contribute to publications and secondments, and be enrolled in a POLITO PhD program. The role emphasizes industrial relevance and scientific excellence.