PhD position in Experimental-Numerical Micro-Mechanics

PhD position in Experimental-Numerical Micro-Mechanics

Published Deadline Location
21 Dec 29 Jan Eindhoven

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Are you an engineer who want to work on sustainability and recycling of material use?
We are looking for a talented and enthusiastic PhD candidate to work on a challenging
experimental-numerical micro-mechanics project, in an exciting multidisciplinary team.

Job description

The overarching project: 'Data Enhanced Physical models to reduce MATerials use' (DEPMAT)

Society calls for an increased recycling of material in steel production processes to reduce the huge CO2 footprint. Current physics-based material models relating composition and thermo-mechanical history are too simple or too computationally expensive for use in industry. DEPMAT aims to develop physics-informed, data-based (machine learning and artificial intelligence) methods for superior accuracy and speed, to enable predictive modelling in industry and to increase recyclability in steel making. We are building a team of talented, enthusiastic researchers to achieve this exciting goal.

PhD vacancy with a focus on in-situ micro-mechanical testing and micromechanical modeling

The goal of this experimental-numerical PhD project is to set up guidelines for providing optimal experimental input for constructing the microstructural part of a physics-informed machine learning approach, with the aim to maximize mechanical accuracy and prediction robustness in light of recycling-induced compositional variations. How to build microstructural models with a minimal level of microstructural detail that finds the optimum between accuracy and computational cost? How to validate accuracy and associated statistical spread of such models, e.g., as function of recycling-induced compositional variations? To this end, you will carry out in-depth microstructural characterization and state-of-the-art in-situ SEM micro-mechanical tests on a few, carefully selected steel grades, to deeply understand their micromechanical behavior. Then you will analyze the mechanical predictions of the physics-informed machine learning approach when trained on different parts of the experimental data, to shed light on the questions above.

Section Mechanics of Materials and the Multiscale Mechanics Laboratory

You will work in the Section of Mechanics of Materials (, Department of Mechanical Engineering, which is globally recognized for its research on experimental analysis, theoretical understanding and predictive modelling of complex mechanical behavior in engineering materials at different length scales (e.g, plasticity, damage, fracture,…), which emerges from the physics and mechanics of the underlying multi-phase microstructure. An integrated numerical-experimental approach is generally adopted for this goal.

You will carry out the state-of-the-art high-resolution in-situ SEM micro-mechanical experiments at the Multiscale Mechanics Laboratory (, led by dr. Johan Hoefnagels (, which bridges the gap between traditional materials science and mechanical characterization labs, by integrating micro-mechanical testing with real-time and in-situ microscopic observation.

You will closely interact with a numerical PhD student, who aims to establish a multiscale data-driven solution procedure exploiting constitutive equations. Part of your work is a statistical confrontation of simulation results against experimental data.


Eindhoven University of Technology (TU/e)


  • A talented, motivated, enthusiastic, curiosity-driven researcher. Deep analytical skills, initiative, creativity, and flexibility are highly desired.
  • A MSc-degree in Mechanical Engineering, Materials science, Physics, or equivalent degree. A strong background in mechanics of materials is required.
  • Experience in experimental mechanics, mechanical testing, micromechanics, microscopy and metallurgy, structure-property relationships, FEM simulations, Matlab coding are of benefit.
  • Interest to work in an interdisciplinary project.
  • Excellent oral and writing skills in English.  

Conditions of employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network with the possibility to present your work at international conferences. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
  • Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities.
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.


  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V35.6170


Eindhoven University of Technology (TU/e)

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De Rondom 70, 5612 AP, Eindhoven

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