Postdoctoral Fellow in Electromechanical Engineering (Ghent University)

Doctoral fellow Last application date: May 24, 2026 23:59 Department: TW08 - Department of Electromechanical, Systems and Metal Engineering Degree: You hold a Master’s degree (preferably) in (electro)mechanical engineering or related engineering fields such as mechatronics or computer engineering Occupancy rate: 100% Vacancy type: Research staff ABOUT GHENT UNIVERSITY Ghent University is a world of its own. Employing more than 15.000 people, it is actively involved in education and research, management and administration, as well as technical and social service provision on a daily basis. It is one of the largest, most exciting employers in the area and offers great career opportunities. With its 11 faculties and more than 85 departments offering state-of-the-art study programmes grounded in research in a wide range of academic fields, Ghent University is a logical choice for its staff and students. YOUR TASKS Our research team - Dynamic Design Lab – works on modelling, control and optimization for mechatronic systems, industrial robots and processes (https://dynamics.ugent.be). We are part of the department of Electromechanical, Systems and Metal Engineering within the Faculty of Engineering of Ghent University (www.ugent.be/ea/emsme/en). We are seeking a highly motivated and talented PhD researcher in the field of system identification and modelling for mechanical/mechatronic systems. You will work on a strategic research project funded by Flanders Make (SBO CausAICA), in which we develop next-generation causal reasoning frameworks for explainable and trustworthy diagnosis of complex industrial systems. A central element of this research is hybrid modelling, which refers to the integration of physics-based system knowledge, experimental data, and probabilistic reasoning into a unified diagnostic framework. By combining first-principles understanding with data-driven learning and probabilistics, we aim to build models that are not only accurate, but also physically interpretable and uncertainty-aware. The PhD project will focus on fault diagnosis and root-cause identification for a web-winding machine, serving as an industrially relevant case study. You will develop and validate causal models on real experimental and simulation data from mechatronic test setups. You will work within the Flanders Make SBO project CausAICA, which aims to establish causal AI methodologies for industrial applications. Your task will be to start from in-house causal model based on hybrid models and explore extensions in an ensemble with other causal methods. You will benchmark your new system identification and modeling tools on real-world data, i.e. wind turbine, motors, winding machine lab setups; with respect to its ability to explain faulty behavior. In the past years our research group has accumulated critical expertise and laboratory infrastructure to support this PhD. You will be responsible for: developing scalable causal discovery and causal inference methods tailored to mechatronic systems validating inferred causal structures and identified root causes against characteristic fault fingerprints obtained from experiments and high-fidelity simulations seeking for industrial and societal impact and adoption of your methodologies presenting your research at conferences and in journals cooperating with researchers active within the research group and outside WHAT WE ARE LOOKING FOR We look for a highly motivated and talented individual with at least some background in electromechanical and computer engineering, having knowledge of real-world mechatronic applications and has system identification and modeling experience. You are quick-witted, have an appetite for working at the intersection of theory and experiments, and willing to apply and/or improve your programming skills You hold a Master’s degree (preferably) in (electro)mechanical engineering or related engineering fields such as mechatronics or computer engineering You have proven experience with modelling and system identification of mechatronic systems You have proven experience in Python You have experience in or understanding of physics-based modelling and data-driven modelling You have experience in mechatronic hardware and software You have a solid foundation in probability and statistics for Bayesian modelling, uncertainty quantification, and causal inference You have a team player mindset, a strong personality and work in a result-oriented manner You are creative and willing to work in a multidisciplinary context You are proficient in oral and written English and have strong communication skills You are willing to extend your network and able to talk on technical matters WHAT WE CAN OFFER YOU We offer a full-time position as a doctoral fellow, consisting of an initial period of 12 months, which - after a positive evaluation, will be extended to a total maximum of 48 months Your contract will start on 01/07/2026 at the earliest The fellowship amount is 100% of the net salary of an AAP member in equal family circumstances. The individual fellowship amount is determined by Team Personnel Administration based on family status and seniority. A grant that meets the conditions and criteria of the regulations for doctoral fellowships is considered free of personal income tax. Click here for more information about our salary scales All Ghent University staff members enjoy a number of benefits, such as a wide range of training and education opportunities, 36 days of holiday leave (on an annual basis for a full-time job) supplemented by annual fixed bridge days, bicycle allowance and eco vouchers. Click here for a complete overview of all the staff benefits Access to state-of-the-art tools and facilities, a network of Flemish companies active in the manufacturing industry, and the possibility to collaborate with other research groups The time to apply and improve your knowledge and skills on state-of-the-art in machine learning, (probabilistic) modelling, system identification and numerical optimization INTERESTED? Send your cv, copy of your diploma (if already in your possession) and a motivation letter to annelies.coene@ugent.be including ‘CAUSAL PHD’ in the email subject before 24/05/2026. If you pass the pre-selection, you will receive further instructions on the selection process and will be invited for an online job interview. We do not accept late applications. As Ghent University maintains an equal opportunities and diversity policy, everyone is encouraged to apply for this position. For more information about this vacancy, please contact Annelies Coene (annelies.coene@ugent.be, +32(0)9/ 264 57 04). If you apply for this position please say you saw it on Computeroxy

Doctoral fellow

Last application date: May 24, 2026 23:59
Department: TW08 - Department of Electromechanical, Systems and Metal Engineering
Degree: You hold a Master’s degree (preferably) in (electro)mechanical engineering or related engineering fields such as mechatronics or computer engineering
Occupancy rate: 100%
Vacancy type: Research staff

ABOUT GHENT UNIVERSITY

Ghent University is a world of its own. Employing more than 15.000 people, it is actively involved in education and research, management and administration, as well as technical and social service provision on a daily basis. It is one of the largest, most exciting employers in the area and offers great career opportunities.

With its 11 faculties and more than 85 departments offering state-of-the-art study programmes grounded in research in a wide range of academic fields, Ghent University is a logical choice for its staff and students.

YOUR TASKS

Our research team - Dynamic Design Lab – works on modelling, control and optimization for mechatronic systems, industrial robots and processes (https://dynamics.ugent.be). We are part of the department of Electromechanical, Systems and Metal Engineering within the Faculty of Engineering of Ghent University (www.ugent.be/ea/emsme/en).

We are seeking a highly motivated and talented PhD researcher in the field of system identification and modelling for mechanical/mechatronic systems. You will work on a strategic research project funded by Flanders Make (SBO CausAICA), in which we develop next-generation causal reasoning frameworks for explainable and trustworthy diagnosis of complex industrial systems. A central element of this research is hybrid modelling, which refers to the integration of physics-based system knowledge, experimental data, and probabilistic reasoning into a unified diagnostic framework. By combining first-principles understanding with data-driven learning and probabilistics, we aim to build models that are not only accurate, but also physically interpretable and uncertainty-aware.

The PhD project will focus on fault diagnosis and root-cause identification for a web-winding machine, serving as an industrially relevant case study. You will develop and validate causal models on real experimental and simulation data from mechatronic test setups.

You will work within the Flanders Make SBO project CausAICA, which aims to establish causal AI methodologies for industrial applications. Your task will be to start from in-house causal model based on hybrid models and explore extensions in an ensemble with other causal methods. You will benchmark your new system identification and modeling tools on real-world data, i.e. wind turbine, motors, winding machine lab setups; with respect to its ability to explain faulty behavior. In the past years our research group has accumulated critical expertise and laboratory infrastructure to support this PhD.

You will be responsible for:

developing scalable causal discovery and causal inference methods tailored to mechatronic systems
validating inferred causal structures and identified root causes against characteristic fault fingerprints obtained from experiments and high-fidelity simulations
seeking for industrial and societal impact and adoption of your methodologies
presenting your research at conferences and in journals
cooperating with researchers active within the research group and outside

WHAT WE ARE LOOKING FOR

We look for a highly motivated and talented individual with at least some background in electromechanical and computer engineering, having knowledge of real-world mechatronic applications and has system identification and modeling experience. You are quick-witted, have an appetite for working at the intersection of theory and experiments, and willing to apply and/or improve your programming skills
You hold a Master’s degree (preferably) in (electro)mechanical engineering or related engineering fields such as mechatronics or computer engineering
You have proven experience with modelling and system identification of mechatronic systems
You have proven experience in Python
You have experience in or understanding of physics-based modelling and data-driven modelling
You have experience in mechatronic hardware and software
You have a solid foundation in probability and statistics for Bayesian modelling, uncertainty quantification, and causal inference
You have a team player mindset, a strong personality and work in a result-oriented manner
You are creative and willing to work in a multidisciplinary context
You are proficient in oral and written English and have strong communication skills
You are willing to extend your network and able to talk on technical matters

WHAT WE CAN OFFER YOU

We offer a full-time position as a doctoral fellow, consisting of an initial period of 12 months, which - after a positive evaluation, will be extended to a total maximum of 48 months
Your contract will start on 01/07/2026 at the earliest
The fellowship amount is 100% of the net salary of an AAP member in equal family circumstances. The individual fellowship amount is determined by Team Personnel Administration based on family status and seniority. A grant that meets the conditions and criteria of the regulations for doctoral fellowships is considered free of personal income tax. Click here for more information about our salary scales
All Ghent University staff members enjoy a number of benefits, such as a wide range of training and education opportunities, 36 days of holiday leave (on an annual basis for a full-time job) supplemented by annual fixed bridge days, bicycle allowance and eco vouchers. Click here for a complete overview of all the staff benefits
Access to state-of-the-art tools and facilities, a network of Flemish companies active in the manufacturing industry, and the possibility to collaborate with other research groups
The time to apply and improve your knowledge and skills on state-of-the-art in machine learning, (probabilistic) modelling, system identification and numerical optimization

INTERESTED?

Send your cv, copy of your diploma (if already in your possession) and a motivation letter to annelies.coene@ugent.be including ‘CAUSAL PHD’ in the email subject before 24/05/2026. If you pass the pre-selection, you will receive further instructions on the selection process and will be invited for an online job interview.

We do not accept late applications.

As Ghent University maintains an equal opportunities and diversity policy, everyone is encouraged to apply for this position.

For more information about this vacancy, please contact Annelies Coene (annelies.coene@ugent.be, +32(0)9/ 264 57 04).

If you apply for this position please say you saw it on Computeroxy

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