Master's Projects
MSc and BSc Projects Spring 2026
You apply by sending your CV and transcript of courses to the contact person by the application deadline. Your e-mail should include a short statement on how your educational profile, experience and interest suit the project.
MgCaZn laser rescanning
Purpose and aim
Mg-alloys are promising materials for resorbable implants. Most current alloys in clinical testing are powder extruded, and contain rare earth elements. 3D-printed MgCaZn is promising to replace current available materials. In order to understand how the printing parameters induce different microstructures in this alloy, laser rescanning experiments and single track analysis are the main focus of this study.
Similar work on other materials.
Project Methods
- Metallic 3D printing
- SEM/EDX characterization
Student profile/background
Master student in material science, additive manufacturing, mechanical engineering or similar.
Contact person: Belén Alonso Rancurel
Deadline: October 31st
Biomaterial-on-chip model for antibiofilm evaluation
Purpose and aim
Current commonly used methods for evaluating the antibacterial properties of biomaterials lack biofilm-based models. Moreover, these evaluations are usually performed using static models, which fail to mimic the real microenvironment encountered when biomaterials are implemented in the body. In this master thesis project, we aim to develop a biomaterial-on-chip model for assessing antibiofilm properties. An antibacterial polymeric bone cement will be used as the base material to be evaluated.
Project Methods
- Microfluidic device fabrication
- Bacteria culture and bacterial viability evaluation
- Microscopy imaging
- 3D printing
Student profile/background
Master student in Biomedical Engineering, Bio and Nano Materials, Biotechnology, Micro- and nanotechnology, or similar.
Contact person: Linglu Hong
Deadline: October 31st
Spheroids on micro-electrode arrays
Description
Electrophysiologically active cells can be mapped by measuring their field potential in a high-definition microelectrode array (HD-MEA) system. In this project, the student will set up a protocol for working with our HD-MEA system for cell culture. The possibilities for measuring on fibroblast spheroids will be investigated.
Project Methods
- Cell culture
- HD-MEA system
- data analysis
Student profile/background
Prior knowledge of cell culture is an advantage, basic electrical engineering
Contact person: Neeraj Katiyar
Physics-Informed Machine Learning for Metal Additive Manufacturing
Purpose and aim
Due to the time required to print and then test additively manufactured components, it is often prohibitively expensive to find the processing parameters (such as laser power and scanning speed) that optimize a material’s characteristic (such as its strength). However, machine learning models can help us better understand the relationship between the process parameters and the resulting part, meaning we do not need to print as many samples. This project will explore new machine learning approaches to model and predict how process parameters influence material properties in additive manufacturing.
Project Methods
- Machine learning model development
- Metallic 3D printing data analysis
- Physics-informed machine learning
Student profile/background
Master student in Computer Science, Machine Learning, Statistics, or similar subject/experience
Contact person: Cole Jetton
Deadline: October 31st
Design of a potential heat treatment criteria for PBF-LB Zn-Mg alloy
Purpose and aim
Powder bed fusion–laser beam (PBF-LB) processing of Zn-Mg alloys is a promising method for fabricating biodegradable implants. However, the resulting microstructure is often inhomogeneous depending on processing conditions. Heat treatment strategies, such as solutionizing can be used to ensure homogeneous distribution of alloying elements. Thermodynamic modelling provides a powerful approach to design heat treatment strategies aimed at microstructural homogenization. More importantly, experimental evaluations will be conducted to validate the modelling results. This will include evaluating the mechanical properties and microstructure associated with each potential heat treatment strategy.
Project Methods
- Thermodynamic modelling
- Evalution of the microstructure (SEM, EDS, XRD...)
- Evalutation of mechanical properties (microhardness, tensile..)
Student profile/background
Master student in materials science, mechanical engineering, additive manufacturing, or similar.
Contact person: Himesha Abenayake
Deadline: October 31st
Towards Process Optimization of lean Mg–Ca–Zn Alloys
Purpose and aim
This project targets process optimization of powder bed fusion–laser beam (PBF-LB) for lean Mg–Ca–Zn alloys as biodegradable implant materials. The alloys offer controlled degradation and biocompatibility, but their additive manufacturing is challenged by oxidation, vaporization, element loss, and printability issues linked to porosity and cracking. By systematically tailoring laser parameters, layer thickness, and scan strategies, the work will minimize defects while preserving alloy composition. Advanced microstructural and basic property evaluation will establish links between processing and microstructure, setting the stage for future assessment of mechanical and corrosion performance.
Project Methods
- Metallic 3D printing
- Microstructural Characterization (OM and SEM)
- Image Analysis.
Student profile/background
Master student in materials science, additive manufacturing, mechanical engineering or similar.