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Job ID
29948

Automation & Robotics Intern

Syensqo is all about chemistry. We’re not just referring to chemical reactions here, but also to the magic that occurs when the brightest minds get to work together. This is where our true strength lies. In you. In your future colleagues and in all your differences. And of course, in your ideas to improve lives while preserving our planet’s beauty for the generations to come.

 

We are looking for:

  • A student who is skilled in one or several of the areas of automation, robotics and machine learning to support applications and research laboratories in the development of innovative products.

We count on you for:

  • Development of machine learning algorithms based on laboratory application scenarios;
  • Contribute to the development of closed-loop scientific discovery platforms.
  • Responsible for system commissioning, code testing and technical documentation writing.
  • Contribute proactively to the global A&R network and build synergies.
  • Collaborate closely with the lab researchers, Artificial Intelligence and Digital Technology teams, to ensure cross pollination of the knowledge and expertise.
  • Other tasks as Manager requires.


You can count on us for:

  • On-job training opportunity plus hands-on experience
  • Open platform to cooperate with different parties for making things happen


You will bring:

  • MS or higher in but not limited to Artificial Intelligence or Computer Science etc.
  • Programming skills in Python, C++, etc.
  • Familiar with common machine learning algorithms (such as defect detection, automatic classification, etc.)
  • Good communication skills in both Chinese and English, and a strong team spirit
  • Experience in building / using laboratory automation systems is preferred
  • Internship for 5 days a week, long-term interns are preferred, with a duration of more than 6 months being ideal

You will get:

  • Competitive salary
  • Free shuttle bus
  • Free lunch and coffee


Additional information:

  • Location: Minhang, Shanghai
  • Onsite working model

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