Requirements
- Master’s level (M2) or engineering degree specialized in computer science, artificial intelligence, data science, or big data
- Solid background in applied mathematics, statistics, and optimization, with an interest in modeling complex systems
- Proficiency in scientific programming, preferably in Python, and experience with data analysis tools such as pandas and scikit-learn
- Fluency in written and spoken scientific English
- Demonstrated autonomy, rigor, organizational skills, initiative, and strong scientific curiosity that supports continuous learning
- Capacity to collaborate effectively in both academic and industrial research settings
Nice to Have
- Familiarity with core artificial intelligence methods including machine learning and deep learning; experience with PyTorch, TensorFlow, or federated learning tools is a plus
- Experience in processing big data and analyzing heterogeneous data, especially sensor-generated time series
- Interest in distributed systems, parallel computing, or real-time data processing architectures
- Understanding of data quality challenges such as noise and missing values, and their impact in industrial applications
Work Arrangement
On-site — Pau, France
