PhD Data Science Intern: Advanced Modeling & ML

PhD Data Science Intern: Advanced Modeling & ML

Full-Time 12 - 16 Β£ / hour (est.) No working from home possible
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At a Glance

  • Tasks: Build analytics systems for virtual experimentation and optimisation in data science.
  • Company: Join Lubrizol Corporation, a leader in sustainable solutions.
  • Benefits: Competitive hourly wage and hands-on experience in a dynamic team.
  • Other info: 12–16 week internship onsite at Hazelwood near Derby, UK.
  • Why this job: Make a real impact on mobility and wellbeing through advanced modelling and machine learning.
  • Qualifications: PhD students in Data Science or related fields with strong analytical skills.

The predicted salary is between 12 - 16 Β£ per hour.

The Lubrizol Corporation invites Ph D students to join its Data Science & Statistics team as interns to build analytics systems for virtual experimentation, optimization, and knowledge discovery.

You will collaborate with a diverse group to deliver sustainable solutions that advance mobility and wellbeing, with internships lasting 12–16 weeks, onsite at Hazelwood near Derby, UK, and a competitive hourly wage.

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PhD Data Science Intern: Advanced Modeling & ML employer: The Lubrizol Corporation

The Lubrizol Corporation is an exceptional employer that fosters a collaborative and innovative work culture, perfect for PhD students eager to apply their skills in data science. Located in Hazelwood near Derby, UK, interns benefit from hands-on experience in advanced modeling and machine learning, alongside opportunities for professional growth and development within a supportive team dedicated to delivering sustainable solutions. With competitive compensation and a commitment to employee wellbeing, Lubrizol stands out as a rewarding place to launch your career.

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Contact Details:

The Lubrizol Corporation Recruitment Team

We think you need these skills to ace PhD Data Science Intern: Advanced Modeling & ML

Data Science
Machine Learning
Analytics Systems Development
Virtual Experimentation
Optimisation Techniques
Knowledge Discovery
Collaboration