Researcher in Machine Learning/Deep Learning applied to Predictive Maintenance
OBSERVABLE UNIVERSE OF THE COMPANY
Our client, a world's leading steel and mining company, is looking for a Researcher in Machine Learning/Deep Learning applied to Predictive Maintenance.
You will be part of the team Digital Transformation Solutions (DTS) which is part of Global R&D Spain center. It is a R&D team devoted to provide digital solutions worldwide for the group. DTS is a multidisciplinary team covering a wide variaty of scientific and business areas with our high qualified researchers (engineers, mathematicians, physicist...), all of them with deep expertise in combining Science and Business Know how.
Their entusiahm and commitment create an incredible working atmosphere for those that want to enjoy the experience of researching and applying breakthrough ideas in a real industrial world.
MISSIONS
You will contribute to develop tool (including UI software) to help maintenance teams on the ArcelorMittal sites (worldwide) to perform their tasks in a most efficient way. Your contribution would be to include a smart signal processing (different sources like vibrations, currents, temperatures, etc..) combined with advanced AI models that will alert the operators when an asset is not performing properly and that will give clues about the source of the problem and the remaining time until a breakage.
We are looking for someone with knowledge of Machine Learning/Deep Learning for predictive maintenance.
You will be in charge of the developpement of different AI Models in collaboration with a signal processing expert.
REQUIRED PROFILE
ACADEMIC SPHERE
Master Degree or PhD in quantitative field: Mathematics, Physics, Engineering, Computer Science, Operations Research or other related field.
TECHNICAL SPHERE
- Experience and solid background in applying Machine Learning/Deep Learning in anomaly detection, time series forecasting, remaining useful life and/or signal processing problems.
- Knowledge of probabilistic models, stochastic processes and generative models desirable.
- Proficiency in at least one object oriented programming language (desirable Python).
- Experience with data wrangling.
- Experience with Condition Monitoring/Predictive Maintenance projects would be desirable.
- Desirable experience with Git, Docker, SQL and noSQL databases, data visualization, Spark and/or cloud computing platforms (Azure, Databricks, AWS, Google Cloud).
SOCIAL SPHERE
- Initiative, Adaptability,
- Results Oriented
- High working autonomy
- Team Work
- Project Management skills
SATELLITE INFORMATION
- Takeoff date: ASAP
- Rocket launch site: Avilés - Spain
- Stellar Benefits: 23+12 day off
- Experience : 2 - 5 years.
- Possibilities of developing a scientific professional career in the company (from researcher to expert).
- Possibility to combine digital knowledge with other strategical fields such as decarbonization, environment, 3d Printing… All these competences are available in Global R&D Spain
Intergalactic guide : Jean-Yves Arrouet
- Département
- Data Science
- Role
- Machine learning, Deep learning, IA (#ai)
- Locations
- Avilés

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Researcher in Machine Learning/Deep Learning applied to Predictive Maintenance
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