Research engineer position in deep learning for reliability and predictive maintenance (H/F)

École polytechnique (also known as “L’X”) is a world-class higher education and research establishment dedicated to sciences and technology, founded in 1794. The School granted a military status in 1804, and operates under the administrative supervision of the Ministry of Armed Forces. École polytechnique is a founding member of Institut Polytechnique de Paris, alongside four other Grandes Ecoles in engineering: ENSAE Paris, ENSTA Paris, Telecom Paris and Telecom SudParis.

École polytechnique is highly internationalized (40% of students and 40% of faculty members are international) and combines top-level research, academics, and innovation at a global level. Its various undergraduate and graduate-level programs – Bachelor of Science, “Ingénieur Polytechnicien” (Master’s level program), Master’s, and PhD – are highly selective and promote a culture of excellence with a strong emphasis on science, anchored in humanist traditions.

With its 23 laboratories, 22 of which are joint research units the French National Center for Scientific Research (CNRS), the École Polytechnique’s research center explores the frontiers of interdisciplinary knowledge to provide significant contributions to science, technology, and society.

Presentation of the research laboratory

The centre for applied mathematics “Le Centre de Mathématiques Appliquées (CMAP)”, aims at the development and the exploration of mathematics in relation with their applications. The opening of the CMAP to other disciplines can be seen through the variety and the complexity of the research topics which are addressed. Its organisation allows the different groups to initiate and explore new topics. The research areas of CMAP are in tight relation with some problematics in physics, mechanics, chemistry, biology and health, finance, but also in social sciences, economics and information technologies. The essence of the research led at CMAP follows the cycle: modelling, mathematical analysis, numerical simulations, visualisation and then refinement of the modelling. Each stage of this cycle draws on the skills of the laboratory's members (80 permanent researchers, doctoral students, numerous visitors and guest researchers).

The lab has also tight links with the Département d’Enseignement-Recherche en Mathématiques Appliquées of Ecole Polytechnique (DepMap), notably through the definition of the teaching and research politics, the recruitment and the participation of the CNRS researchers to the teaching in applied mathematics (in the engineer curriculum as well as the Master's degrees). The CMAP has strong interactions with some industrial and financial companies, through multiple research grants and fundings of Ph.D.'s (CIFRE), and through different teaching and research "chaire" programs.

We are looking for: Research engineer position in deep learning for reliability and predictive maintenance (H/F) – Fixed-term contract for 2 years.

Context:

This position is open within the framework of the Chair “AI and Predictive Maintenance”(IAMP) supported by Ecole polytechnique and sponsored by Europorte.

Project description:

The nowadays advance in sensing and data acquisition technologies enable the collection of heterogenous and large amounts of monitoring data from the industrial components and systems along their entire life, during different operating regimes, and under varying environmental conditions. The efficient analysis and processing of such data using advanced machine learning and artificial intelligence techniques can provide valuable indicators about the industrial component/system health, safety, and reliability. These indicators, eventually, contribute to the overall availability and profitability of the industrial facility.

In this context, the chair IAMP is offering 2-years contract for a highly skilled and motivated research engineer. The successful candidate will contribute to cutting-edge research projects focused on developing advanced methods and software based on deep and transfer learning algorithms to improve fault detection, diagnosis and prognosis, health management, and predictive maintenance of industrial components and systems.

In this role, you will be responsible for the following main tasks:

• Develop innovative methods and software based on deep and transfer learning techniques, targeting Prognostics and Health management (PHM) and predictive maintenance problems.

• Write scientific articles and publish research findings in top conferences and journals.

• Support master and doctoral researchers.

• Advise interns and trainees, and supervise collective scientific projects.

• Develop innovative pedagogies in statistical learning, artificial intelligence and their applications in industry.

This post is to be filled in Palaiseau (Essonne) by secondment or contract.

We're made for you because :

École Polytechnique’s strategic model is based on three pillars: education, research and innovation.

Innovation and entrepreneurship plays an important role for the School’s development. A start-up incubator has been launched in 2015 to support the creation of start-ups, namely in Deep Tech.

Ever keen to attract the best talents amongst its students, faculty, research and administrative staff, École Polytechnique is resolutely committed to promoting social and gender diversity and equality.

École Polytechnique is committed to Sustainability. Alongside its partners at Institut Polytechnique de Paris, the School employs education, research, and innovation to further the knowledge of the evolution of ecosystems and climate change and to develop new solutions for sustainable and inclusive prosperity that respond to current needs without compromising the future of the coming generations.

 Why you should join us :

Joining us means joining an internationally renowned institution, discovering a wide variety of professions and accessing great career potential.

École polytechnique is actively committed to sustainable development and social responsibility. Defending equal opportunity, promoting diversity in different forms and reducing environmental impact are all at the heart of the school’s strategic ambitions.

We offer our employees many advantages:

• 25 days of annual leave + up to 18 days of RTT (the reduction of working time scheme provides for the allocation of days of rest to an employee whose working time is more than 35 hours per week).

• The possibility to work remotely several days.

• Up to 50% reimbursement of public transport costs.

• Access to on-campus services (staff canteen, library, L’X Museum, postal service, hairdresser).

• Access to health services: physiotherapist, free osteopath, medical center, social worker on-site.

• Access to sports facilities (swimming pool, tennis courts, gym, etc.) and activities at a preferential rate.

• A €15 contribution to your health insurance provider.

You are our rare pearl because :

You hold a PhD degree in statistical learning, machine learning, deep learning or related topics (preferably applied for solving industrial and engineering problems).

You possess knowledge of the various tools used in artificial intelligence, machine learning and data science, such as classification, clustering, regression, feature extraction/selection, uncertainty and sensitivity analysis.

You demonstrate proficiency in deep learning tools such as MATLAB and Python (TensorFlow, PyTorch or Keras).

You have experience in handling and analysing real data, particularly time series data.

You exhibit the ability to work effectively both independently and collaboratively as part of a team.