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UCLouvain

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Fully Funded PhD in Machine Learning and Statistics at UCLouvain UCLouvain

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

Jul 31, 2026

Country

-

University

UCLouvain

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Keywords

Computer Science
Data Science
Mathematics
Artificial Intelligence
Probabilistic Modeling
Explainable Ai
Optimisation
Econometric
Statistics
Machine learning

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About this position

UCLouvain in Belgium is advertising a fully funded PhD position in Machine Learning and Statistics.

The project sits at the intersection of machine learning, statistical learning, artificial intelligence, probabilistic modeling, Bayesian methods, optimization algorithms, trustworthy AI, explainable AI, data science, and applied statistics. The research aims to develop novel machine learning and statistical methods with strong theoretical foundations while also addressing real-world data science challenges.

Applicants are encouraged from backgrounds in Computer Science, Artificial Intelligence, Statistics, Mathematics, Data Science, Machine Learning, or related areas. The post highlights the importance of strong mathematical foundations, programming skills, and research motivation.

Eligibility requirements include a Master’s degree in a relevant field, strong programming ability in Python or similar languages, and a solid background in probability, statistics, and machine learning.

Funding is described as fully funded, with additional support for conference travel and publication. The post does not specify stipend amount or tuition details.

The application deadline is 31 July 2026. Interested candidates should email their application materials to [email protected] and consult the linked information page for more details.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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