Publisher
source

Mohammed VI Polytechnic University

Postdoctoral Researchers in Artificial Intelligence (AI) – Large Language Models for Predictive Maintenance Mohammed VI Polytechnic University

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available

Country

-

University

Mohammed VI Polytechnic University

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Keywords

Computer Science
Information Technology
Deep Learning
Artificial Intelligence
Natural Language Processing
Time Series Analysis
Anomaly Detection
Statistics
Large Language Models
Machine learning
AI industry

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About this position

Mohammed VI Polytechnic University (UM6P) in Benguerir, Morocco is seeking a highly motivated postdoctoral researcher in Artificial Intelligence, with a strong emphasis on Large Language Models (LLMs) for predictive maintenance. The position sits within an applied research context where advanced AI methods are being developed to analyze unstructured industrial data such as maintenance logs, sensor streams, and technical reports.

The successful candidate will contribute to innovative research at the intersection of AI, NLP, and industrial systems. The work includes developing and fine-tuning LLMs, exploring anomaly detection and failure prediction, and supporting optimization of maintenance schedules. The role also involves collaborating with domain experts to translate model outputs into scalable and interpretable solutions for real-world deployment.

UM6P presents itself as a research- and innovation-driven university with a strong mission to support African development. Based in the Green City of Benguerir, the university aims to strengthen its international research profile while fostering skills relevant to future industrial and digital challenges.

Applicants are expected to have recently completed, or be close to completing, a PhD in Computer Science, Machine Learning, Natural Language Processing, or a closely related area, with a thesis focused on AI and LLMs. A strong publication record in leading venues such as NeurIPS, ICML, ACL, or EMNLP is preferred. Practical experience in Python and deep learning frameworks such as TensorFlow, PyTorch, or JAX is required, along with a solid understanding of transformer architectures and fine-tuning techniques. Experience with time-series data, industrial datasets, predictive maintenance, or anomaly detection is a strong advantage.

To apply, candidates should prepare a cover letter explaining their research interests and fit for the project, a current CV including publications, contact details for at least three references, and a short research statement of up to two pages describing past work and future directions related to LLMs. The posting does not specify a deadline, so applicants should consult the application portal promptly.

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.

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