PhD - AI and In-situ Monitoring for Hybrid 3D Printing

1 - Working at the VUB

For more than 50 years, the Vrije Universiteit Brussel has stood for freedom, equality and solidarity, and this is very much alive on our campuses among students and staff alike. 

 

At the VUB, you will find a diverse collection of personalities: innovators pur sang, but above all people who are 100% their authentic selves. With some 4,000 employees, we are the largest Dutch-speaking employer, in the private sector, in Brussels; an international city with which we are only too happy to connect and where (around) our 4 campuses are located. 

 

Add to this our principle of free research - in which self-reflection, a critical attitude and an open, creative mind around scientific and social issues are central - and you have a university that is fundamentally groundbreaking and pioneering in education and research. In short: the VUB all over again. 

 

Moreover, the VUB is a member of EUTOPIA, an alliance of like-minded European universities, all ready to reinvent themselves.

2 - Position description

The Faculty of Engineering, Department Toegepaste mechanica, is looking for a PhD-student with a doctoral grant. 

 

More concretely your work package, for the preparation of a doctorate, contains: 

The Department of Mechanical Engineering and the AI research group at the Vrije Universiteit Brussel (VUB) are looking for a PhD candidate to contribute to research on the optimization of a hybrid, laser-based Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth data through advanced ex-situ measurement technologies. The group’s ambition is to develop a robust framework for capturing high-quality data from their in-house hybrid additive-subtractive research platform.

 

Initially, a black box deep learning approach will be implemented. However, due to the need for robustness, transparency, and explainability (e.g. for quality control across sectors), the research will transition in a second phase to white box approaches that result in interpretable models. For ground truth data, μCT data will be used. A similar approach will be applied using surface roughness measurements from optical techniques such as white light interferometry.

 

The selected candidate will contribute to the group’s R&D output and carry out the following tasks over the 4-year PhD:

• Perform 3D printing tests using the in-house developed data acquisition system as an in-situ monitoring solution. Validate and refine the system to improve data capture. Investigate feature engineering techniques to identify links between extracted features and representative printing artifacts or process anomalies. For example, hyperspectral data may be translated into melt pool temperature features or temperature fields.

• Integrate a new measurement solution to deepen understanding of the metal 3D printing process and link with ex-situ inspection systems.

• Apply deep and shallow supervised learning methods to the collected dataset. Deep learning will focus on physics-based features developed earlier. Convolutional layers will be used to extract spatial patterns, while LSTM layers will capture temporal aspects across image sequences.

• As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights from data analysis.

• First, binary classification models will be trained using μCT data to distinguish between acceptable and defective parts. Porosity size will be used to define acceptable vs. unacceptable flaws. Models will be benchmarked for speed, accuracy, and interpretability.

• Next, multi-class classification will be developed for various defects and anomalies (e.g., lack of fusion, porosity, spatter, size). The research will evaluate whether a single model suffices or if subclassification using multiple models is required.

 

For this function, our Brussels Humanities, Sciences & Engineering Campus (Elsene) will serve as your home base. 

3 - Profile

What do we expect from you?

 

• A master’s degree in Mechanical or Materials Engineering or,

  a master’s degree in Artificial Intelligence or,

  a master’s degree in Computer Science/Engineering.

 

• You hold a master’s degree in Mechanical or Materials Engineering and are motivated to contribute to innovations in advanced manufacturing and AI. Or, you have a degree in Artificial Intelligence or Computer Science/Engineering and are eager to develop AI models for additive manufacturing.

  The ideal candidate:

  • Is motivated to become an expert in (hybrid) additive manufacturing, advanced measurement technologies, and AI

  • Has practical skills for conducting experimental work, implementing monitoring solutions, and adapting hardware on the research platform

  • Has a strong analytical mindset

  • Has programming skills in Matlab and/or Python for data acquisition, processing, and visualization

  Experience in the following areas is considered a plus: machine learning, additive manufacturing, machining, residual stress, optical measurement techniques, CAD/CAM, toolpath planning, etc.

 

• You have not performed any works in the execution of a mandate as an assistant, paid from operating resources, over a total (cumulated) period of more than 12 months.

 

The VUB wants to be a reflection of the society where everyone's talent is valued, regardless of gender, age, religion, skin color, migration background, disability and neurodiversity.

4 - Offer

Are you going to be our new colleague?

 

You’ll be offered a full-time PhD-scholarship, for 12 months (extendable up to max. 48 months, on condition of the positive evaluation of the PhD activities), with planned starting date 01/09/2025. 

 

You’ll receive a grant linked to one of the scales set by the government.

 

IMPORTANT: The effective result of the doctorate scholarship is subject to the condition precedent of your enrolment as a doctorate student at the university.

 

At the VUB, you’re guaranteed an open, involved and diverse workplace where you are offered opportunities to (further) build on your career.

 

As well as this, you will also enjoy various other benefits:

• Extensive homeworking options, a telework allowance of 50 euros per month OR an internet fee of 20 euros per month;
• An open and informal working environment where attention is paid to work-life balance, and exceptional holiday arrangements with 35 days of leave (based on a fulltime contract), closure between Christmas and New Year and 3 extra leave days;
• Cost-free hospitalisation insurance;
• Full reimbursement of your home-to-work commute with public transport according to VUB-policy, and/or compensation if you come by bike; 
• A wide selection of meals in our campus restaurants at attractive prices;
• Excellent and affordable facilities for sport and exercise, a range of discounts via Benefits@Work (in  all kinds of shops, on flights, in petrol stations, amusement parks...) and Ecocheques; 
• Nursery near campus, discount on holiday camps; 
• The space to form your job content and to continuously learn through our VUB learning platforms and training courses;
• And finally: great colleagues with a healthy drive.

5 - Interested?

Is this the job you’ve been dreaming of?

 

Then apply, at the latest on 31/07/2025, via jobs.vub.be, and upload the following documents:

• your CV;
• your motivation letter;
• your diploma (not applicable for VUB alumni).

 

Do you have questions about the job content? Contact Dieter De Baere at 0032497188646 or on Dieter.De.Baere@vub.be.

 

Would you like to know what it’s like to work at the VUB? Go to jobs.vub.be, and find all there is to know about our campuses, benefits, strategic goals and your future colleagues.

 

Would you like more information about EUTOPIA? Go to eutopia-university.eu, and read more about the role of the VUB in the development of the EUTOPIA alliance.