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Mohammed VI Polytechnic University

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COLCOM - Postdoctoral in Machine Learning Mohammed VI Polytechnic University in

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

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Country

Mohammed VI Polytechnic University

University

Mohammed VI Polytechnic University

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Keywords

Computer Science
Mathematics
Probability Theory
Linear Algebra
Clustering Algorithms
Dimensionality Reduction
Statistics
Machine learning

About this position

The Data Intelligence Group at the College of Computing, Mohammed VI Polytechnic University (UM6P), is offering two postdoctoral positions in machine learning. Located in Benguerir, Morocco, UM6P is a modern institution dedicated to research and innovation, serving Morocco and the African continent. The College of Computing provides world-class education in computer science and fosters discovery and innovation, with a strong emphasis on research excellence.

The Data Intelligence Group is recognized internationally for its expertise in data management and machine learning, maintaining a robust network of collaborators in academia and industry. The postdoctoral fellows will contribute to projects in multimodal representation learning and retrieval, focusing on developing novel machine learning algorithms for representation learning, dimensionality reduction, clustering, and search. Responsibilities include conducting theoretical and experimental analyses, publishing in high-quality venues, presenting at scientific events, supervising students, assisting in research proposal writing, contributing to teaching and course development, and organizing workshops and seminars.

Applicants must have a Ph.D. in Computer Science, Applied Mathematics, or a related field, with a strong publication record in machine learning. Preferred expertise includes representation learning, deep embeddings, contrastive learning, and foundation models. Candidates should possess a solid background in linear algebra, probability, and statistics, strong programming skills with deep learning frameworks (such as PyTorch), and familiarity with data structures, algorithms, and search or indexing techniques. Excellent communication, analytical, teamwork, and organizational skills are essential. Final-year Ph.D. students expecting to graduate by September 2026 are also encouraged to apply.

Applications should be submitted online and emailed to [email protected]. Materials must include an up-to-date CV and a zipped archive with a cover letter and full transcripts. The CV should detail high-school degree type, overall high-school average, Mathematics grade in the national exam, and university ranking. The position offers a one-year renewable contract, with the expected start date of February 1st, 2026. The university provides a vibrant research environment with opportunities for collaboration and professional development.

For further information and to apply, visit the application link provided. Join UM6P’s Data Intelligence Group to advance your research career in machine learning and contribute to impactful projects in a dynamic academic setting.

Funding details

Available

What's required

Applicants must hold a Ph.D. in Computer Science, Applied Mathematics, or a related field. A strong publication record in machine learning is required, with preference for expertise in representation learning, deep embeddings, contrastive learning, or foundation models. Candidates should have a solid background in linear algebra, probability, and statistics, as well as strong programming skills with deep learning frameworks such as PyTorch and standard data analysis tools. Familiarity with data structures, algorithms, and ideally search or indexing techniques is expected. Excellent communication, analytical, teamwork, and organizational skills are essential. Final-year Ph.D. students may apply if they expect to obtain their degree by September 2026. The CV must include high-school degree type, overall high-school average, Mathematics grade in the national exam, and overall average/ranking in university studies.

How to apply

Submit your application online and email your materials to [email protected] with the subject '[Postdoctoral Fellow Position]'. Include an up-to-date CV and a zipped archive containing a cover letter and full transcripts. Ensure your CV details your high-school degree, averages, and university ranking. Ph.D. students expecting to graduate by September 2026 are eligible.

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