PhD Student in Hybrid Algorithms: Combining Deep Learning and Physical Models
Chair of Intelligent Maintenance Systems
vor 1 Tg.

Job description

The main objective of the PhD project is to develop methodology that enables fusing physical models and deep learning algorithms for optimal operation and maintenance of complex industrial systems.

The research will build upon our previous research in this field and will develop the methodology further. Limited teaching responsibilities are also included in this position.

We expect the candidate to be self-driven with strong problem solving abilities and out-of-the-box thinking.

Your profile

We are looking for a PhD with a strong analytical background, and an outstanding MSc degree in Engineering, Control, Computer Science, Physics, Applied Mathematics, or a related field.

The candidate should be proficient in machine learning, deep learning, signal processing, statistics and learning theory.

Experience in reinforcement learning is beneficial. Professional command of English (both written and spoken) is mandatory.

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