Summary
The University of Leuven (KU Leuven) and the Free University of Brussels (VUB) invite applications for a PhD position in a collaborative research project focused on developing machine learning-based computational models for predicting chromatographic retention behavior. The project aims to automate method development in analytical chemistry through innovative approaches that integrate reinforcement learning and human-based modeling.
PhD Position in Machine Learning –Driven Chromatographic Retention Modeling, Belgium
Designation
PhD Candidate
Research Area
- Machine Learning
- Chromatographic Retention Modeling
- Analytical Chemistry
- Pharmaceutical Sciences
- Chemical Engineering
Location
Gasthuisberg Campus, Leuven, Belgium (collaboration with VUB)
Eligibility/Qualification
- Master’s degree in (Analytical) Chemistry, Pharmaceutical Sciences, Bio- or Chemical Engineering, or a related field
- Strong interest in analytical chemistry
- Hands-on experience with (U)HPLC (essential)
- Familiarity with mass spectrometry (desirable)
- Experience in Python or other scientific programming tools
- Strong analytical mindset and willingness to work across experimental and computational domains
- Proficient in oral and written English
Job Description
The selected candidate will:
- Work closely with research groups at both KU Leuven and VUB
- Conduct fundamental investigations into liquid chromatography supports
- Implement multidimensional liquid chromatography techniques in conjunction with mass spectrometry
- Develop automatable method development strategies for complex samples
- Design and test algorithms for method development using machine learning techniques
- Engage in a cross-disciplinary research environment combining analytical chemistry and machine learning
How to Apply
Interested candidates should submit their CV and a motivation letter using the KU Leuven online application tool.
Last Date to Apply
May 29, 2026, 23:59 CET
| Field | Details |
|---|---|
| Title | PhD Position in Machine Learning–Driven Chromatographic Retention Modeling |
| Summary | Developing computational models to automate method development using machine learning. |
| Designation | PhD Candidate |
| Research Area | Machine Learning, Chromatographic Retention Modeling, Analytical Chemistry, etc. |
| Location | Gasthuisberg Campus, Leuven, Belgium |
| Eligibility/Qualification | Master’s degree in relevant fields, strong analytical skills, programming experience |
| Job Description | Conduct research, implement chromatography techniques, develop algorithms |
| How to Apply | Submit application via KU Leuven online application tool |
| Last Date to Apply | May 29, 2026, 23:59 CET |
For further details, please contact Prof. Dr. Deirdre Cabooter at deirdre.cabooter@kuleuven.be.
