Researcher Engineer in Reinforcement Learning (100 % ETP)

Job title:

Researcher Engineer in Reinforcement Learning (100 % ETP)

Company:

Adoc Talent Management

Job description

Recognised as a Centre of excellence internationally, our client develops and integrates emerging technologies in the industrial sector. These technologies are articulated around four areas of activity: Networks & Telecoms, Applied Photonics, Artificial Intelligence & Embedded Systems, and Rail Certification.Within the Artificial Intelligence and Embedded Systems department, the Artificial Intelligence team plays a crucial role in supporting companies (from start-ups to corporates) in their technological innovation projects. They accompany them from the feasibility phase to the development of minimal viable products in various fields such as avionics, automotive, IoT, Smart Cities, Industry 4.0, medical sciences, and defence.To strengthen their AI team, we are looking for a Research Engineer in Reinforcement Learning.ObjectiveYou will engage in pioneering research in machine and deep learning (RL), applying your expertise across diverse fields such as AgroTech, Defense, Health, and Smart Cities to solve optimization problems.You will develop innovative solutions to large-scale real-world challenges, leveraging advanced technologies to make a significant impact in a variety of sectors.You should be able to work on a project where the RL system is already designed and work on the explicability of this model.Main Responsibilities and Tasks

• Contribute to R&D projects to develop trusted RL algorithms.
• Must be able to work on a project where the RL system has already been designed and work on the explicability of this model
• Participate in cutting-edge research in machine/deep learning applications in various fields (AgroTech, Defence, Health, Smart Cities, etc.).
• Develop solutions for real-world, large-scale problems.
• Work internally with various teams.
• Make presentations to different audiences (industrial partners, scientists, etc.).

Expected QualificationsEducation: Master’s or PhD in a quantitative discipline, e.g., Computer Science, Mathematics, Operations Research, Data Science, or equivalent practical experience.Knowledge:

• Extensive knowledge in Reinforcement Learning, Mathematics, and Statistics.
• Familiarity with Python libraries and toolkits such as PyTorch, Ray RLlib, TorchRL, Matplotlib, Pandas, Scikit-learn, Tensorflow, OpenAI Gym, Baseline3, etc.
• Experience with the Linux operating system.
• Trustworthy RL (including explicability, XRL) is an asset

Skills:

• Scientific thinking and the ability to work with literature.
• Ability to conduct a good scientific watch.
• Capability to implement complex tech solutions.
• Good written communication skills (presentation).
• Fluency in English (spoken and written).
• Autonomy and good self-organization.
• Good listening skills.
• Teamwork spirit.
• Ability to develop good relationships and communication with colleagues and industrial partners.
• Sensitivity to quality and safety.

What do they offer?They provide an exciting work environment with a salary aligned with market standards and an attractive benefits package. You will engage in highly stimulating and impactful projects across diverse themes and with various partners. The applications span multiple industries, offering you the freedom to act and autonomy in your work. The company supports your growth and skill development, promoting continuous learning. The company values collaboration, flexibility, and working together with universities and industry labs throughout the entire R&D chain. You’ll be part of a team that upholds strong values and fosters a collaborative interface.Why You Should ApplyDo you want to contribute to driving AI innovation forward and join a great, dynamic, and growing team? Then, tell us what makes you the perfect match.If you feel you are a good fit for the role and the company, please send your application (CV and cover letter) to Adoc Talent Management.

Expected salary

Location

Mons, Hainaut

Job date

Thu, 01 Aug 2024 04:31:40 GMT

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