The modeling of complex engineering systems is highly challenging. Physics-based models require a cautious application of constitutive assumptions, whereas data-based models require vast amounts of data. The research project "DAMOCLES; Data-Augmented Modeling Of Constructive Laws for Engineering Systems", of which this PhD position is a part, targets a breakthrough in the constitutive modeling of such systems in different physical domains by developing a unified multi-tool framework that combines the favorable characteristics of physics-based and data-based approaches. DAMOCLES is an inter-departmental project part of the Eindhoven Artificial Intelligence Institute (EAISI) Exploratory Multidisciplinary AI Research Program (EMDAIR).

The DAMOCLES project is divided into three interlinked sub-projects of which one project is advertised here. The other DAMOCLES vacancies are:

• Deep learning with Physics Based Constraints for the Identification of Engineering systems
• Robust Bayesian uncertainty quantification

This open PhD position aims to construct a robust constitutive modeling framework from a set of available state-of-the-art phenomenological models that can adopt to a wide range of material characteristics of different physics, while emulating various levels of nonlinearity and hysteresis, such that the properties of complex systems can be identified in a noninvasive way. 

Constitutive laws of materials mimic the observed microscopic phenomena at the macroscopic level. The appropriate material model is quantified by fitting its parameters to mimic the material response in a specific engineering application. Furthermore, the data which are usually acquired on simplified geometries, or samples, are far from representative for the final designs. Due to the manufacturing process (heating, cutting, stresses after assembly), large discrepancies are expected between the sample-predicted and the effective material characteristics of the final design. The PhD candidate will develop methods and identification algorithms which will characterize the material behavior in engineering system with increasing complexity. Special focus is dedicated to material responses in magnetic, electric (piezo) and mechanical domains subject to hysteresis behavior. The candidate will adopt existing state-of-art models possessing necessary properties such as congruency, rate-dependency or memory and recombine them for a specific application using evolutionary algorithms.

To accomplish the objectives of the DAMOCLES project, a strong cooperation with the PhD candidates and researchers in the other sub-projects is required. In particular, the results obtained in this PhD project will be evaluated and analyzed on a selected set of overarching benchmark applications.

Tasks

• Literature study of system identification and constitutive modeling with focus on hysteresis.
• Establish an environment where the constitutive models are interpretable and allow for an efficient search space exploration.
• Employ evolutionary algorithms to recombine the models targeting a specific application.
• Exploration of the identification steps for the developed methods and design of experiments for validation purposes.
• Dissemination of the results of your research in international and peer-reviewed journals and conferences.
• Writing a successful dissertation based on the developed research and defending it.
• Assume educational tasks like the supervision of Master students and internships.
• Successful integration in the Eindhoven Artificial Intelligence for Systems Institute.

We are looking for a candidate who meets the following requirements:

• You are a talented and enthusiastic young researcher.
• You have experience with or a strong background in physics, mathematics, and statistics. Preferably you finished a master's in (Applied) Physics, (Applied) Mathematics, Statistics, Systems and Control, Electromechanical Engineering, Mechanical Engineering or Electrical Engineering.
• You have good programming skills and experience (Python is an asset).
• You have good communicative skills, and the attitude to partake successfully in the work of a research team.
• You are creative and ambitious, hard-working, and persistent.
• You have good command of the English language (knowledge of Dutch is not required).

• A challenging job in a highly motivated team at a dynamic and ambitious university and a stimulating internationally renowned research environment.
• You will be part of a highly profiled multidisciplinary collaboration where expertise of a variety of disciplines comes together.
• A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
• To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
• To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
• A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.

The TU/e is located in one of the smartest regions of the world and part of the European technology hotspot 'Brainport Eindhoven'; well-known because of many high-tech industries and start-ups. A place to be for talented scientists!