PhD Student

Last application date
Jul 31, 2021 00:00
TW06 - Department of Electronics and Information Systems
Limited duration
Master degree (The project sits at the interface of Machine Learning, Visual Analytics, and Biomedical applications)
Occupancy rate
Vacancy type
Research staff

Job description

The DAMBI (VIB & Ghent University) and AIDA (Ghent University IDLab) research groups are looking for 1 or 2 qualified and motivated candidates to develop machine learning methods and visualization techniques for the analysis of biological data, such as single-cell data, in the direction of using prior knowledge in data analysis. The project sits at the interface of Machine Learning, Visual Analytics, and Biomedical applications. Up to two fully funded positions as PhD student (4 years) are available.

The project comprises fundamental research in machine learning and data visualization, focused on analytics for biological/biomedical data. The aim is to develop algorithms and tools that enable the use of prior knowledge in modelling and visual analytics of biological data. Challenges include the design of embedding methods and systems to support interactive data analysis, and their evaluation.

The research will be supervised by Prof. Jefrey Lijffijt, Prof. Yvan Saeys, and Prof. Tijl De Bie in a joint position in the AIDA and DAMBI groups (; We are engaging international teams with a track record in world-leading research in immunology, bioinformatics, data mining, and machine learning.

Ghent University is a comprehensive internationally leading research-intensive university. English is the working language; knowledge of Dutch or French is not required. The university also offers a wide range of courses for skills professionalization (academic and beyond). Ghent is a historical, vibrant, and internationally minded city in Belgium with 250k inhabitants.

Job profile

You will need to hold a relevant master’s degree with demonstrated first-class performance (e.g., outstanding grades, thesis result, or publications). The ideal candidate would demonstrate mastery of the core aspects of machine learning:
● Fundamentals of probability and statistics
● Algorithm design, discrete/continuous optimisation
● Programming (in Python, C++/Java, JavaScript, …)
Experience with data visualization, user interfaces, and cell biology is a plus.

How to apply

Applications may be sent by email to Please include cover letter, CV, and contact details of 1 to 3 referees. Do not include reference letters, these will be solicited by us. Suitable candidates will be invited for an interview and may get a small assignment. Applications remain welcome until the post is filled.