Doctoral researcher in Machine Learning Algorithms Efficiency

About Us

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.

The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we live in.

Your role

We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training costs and energy requirements of state-of-the-art deep learning models significantly, while democratizing them for a vast community of users, researchers, and practitioners. The task is to perform just high-risk/high-gain research without any teaching obligations.

The position is funded through the support of Google.org (more details here).

Our group performs fundamental and applied research in many aspects of machine learning focusing on efficiency, generalization, and sparse neural networks. Currently we are expanding our expertise by applying our theoretical findings also to robotics. Hybrid is our usual way of working and the language of communication is English. Our current team members are spread across three universities (University of Luxembourg, Eindhoven University of Technology, and University of Twente). The graduated PhD students supervised by Decebal have become research and team leaders themselves and have been hired at prestigious institutions such as Google DeepMind, ELLIS Institute, Max Planck Institute for Intelligent Systems, VU Amsterdam, TU Eindhoven, UT Austin, or the University of Oxford.

In addition, our group has excellent collaborators world-wide. Summer schools and research visits are encouraged and supported. Industrial internships are appreciated. We publish regularly in top scientific venues for AI such as NeurIPS, ICML, ICLR, IJCAI, AAMAS, AISTATS, ECMLPKDD, GECCO, ECAI, UAI, Neurocomputing, Machine Learning journal, Transactions on Machine Learning Research, Nature Communications, and so on.

The successful applicant will be supervised by Decebal Mocanu. For informal enquiries, please contact [email protected]

Your profile

• BSc (graduated) and MSc (graduated or close to graduation) in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Applied Mathematics, or related fields.
• Scientific curiosity and creative thinking
• Ambition to publish or experience in publishing at A* level conferences
• Strong programming and problem-solving skills
• Analytical mindset, hard worker, and team player
• Experience in a research or industrial environment is a plus
  
  

Language Requirements:

Applicants must demonstrate at least B2-level proficiency in the language of their thesis. For details and accepted certificates, please visit the Application for admission – Doctoral Candidates.

We offer

• Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the “University of the Greater Region” (UniGR)
• A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site with excellent infrastructure
• A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs …
  
  

How to apply

Applications should include:

• Curriculum Vitae, including your contact details, educational record, work experience (if available), publications (if available), awards (if available), and English language test results (optional).
• Cover letter presenting your motivation for this doctoral thesis topic, and explaining how your qualifications and aspirations align with its academic focus
• Transcript of all modules and results from university-level courses taken
• Names and contact details of 2-3 referees. Just the referees of the short-listed candidates will be contacted
  
  

Early application is highly encouraged, as the applications will be processed upon reception. To ensure full consideration, candidates should apply by 16 April 2026 ONLINE formally through the HR system. Applications by Email will not be considered.

All qualified individuals are encouraged to apply. In line with our values, the University of Luxembourg promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students.

General information:

• Contract Type: Fixed Term Contract 36 Month
• Work Hours: Full Time 40.0 Hours per Week
• Location: Belval Campus
• Internal Title: Doctoral Researcher
• Job Reference: UOL08030
  
  

The yearly gross salary for every PhD at the UL is EUR 41976 (full time).