University of Luxembourg
1 week ago
Doctoral researcher in Machine Learning Algorithms Efficiency University of Luxembourg in Luxembourg
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Apr 16, 2026
Country
Luxembourg
University
University of Luxembourg

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About this position
The University of Luxembourg, a leading international research university, is offering a PhD position for a doctoral researcher in Machine Learning Algorithms Efficiency. The Faculty of Science, Technology and Medicine (FSTM) provides a multidisciplinary environment, with expertise spanning Mathematics, Physics, Engineering, Computer Science, Life Sciences, and Medicine. This position is based at the Belval Campus, a modern urban site with excellent infrastructure and close ties to both the business world and the Luxembourg labour market.
The doctoral researcher will focus on fundamental research to develop truly sparse solutions for dynamic sparse training on both CPU and GPU platforms. The aim is to significantly reduce the training costs and energy requirements of state-of-the-art deep learning models, making them more accessible to a wider community of users, researchers, and practitioners. The research is high-risk/high-gain and does not involve teaching obligations, allowing the candidate to concentrate fully on innovative algorithmic development.
Supervision will be provided by Dr. Decebal Mocanu, an expert in the field. The successful candidate will join a diverse and international team, benefiting from the university's multilingual character and its partnerships with European institutions, innovative companies, and numerous non-academic partners.
Applicants should hold a BSc (graduated) and MSc (graduated or close to graduation) in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Applied Mathematics, or related fields. Essential qualities include scientific curiosity, creative thinking, ambition to publish at A* level conferences, strong programming and problem-solving skills, an analytical mindset, and the ability to work both independently and as part of a team. Experience in a research or industrial environment is advantageous. Language requirements include at least B2-level proficiency in the language of the thesis, with accepted certificates as specified by the university.
The position offers a fixed-term contract of 36 months, full-time (40 hours per week), with a yearly gross salary of EUR 41976. The University of Luxembourg promotes an inclusive culture and encourages applications from individuals of all backgrounds, upholding equality and respect for employees and students.
To apply, candidates should submit their curriculum vitae, cover letter, transcripts, and names of 2-3 referees online through the HR system. Early application is encouraged, as applications are processed upon reception. The deadline for full consideration is 16 April 2026. Applications by email will not be considered.
This opportunity is ideal for motivated researchers seeking to advance the efficiency of machine learning algorithms in a dynamic and supportive academic environment.
Funding details
Available
What's required
Applicants must have a 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, 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 are required. Experience in a research or industrial environment is a plus. Applicants must demonstrate at least B2-level proficiency in the language of their thesis, with accepted certificates as specified by the university.
How to apply
Apply online through the HR system by submitting your CV, cover letter, transcripts, and names of 2-3 referees. Early application is encouraged as applications are processed upon reception. Applications by email will not be considered. Ensure full consideration by applying before 16 April 2026.
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