Data Scientist Intern (PhD level)

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profile Job Location:

Derby - UK

profile Monthly Salary: Not Disclosed
Posted on: 11 hours ago
Vacancies: 1 Vacancy

Job Summary

Header: About Lubrizol

The Lubrizol Corporation a Berkshire Hathaway company is a specialty chemical company whose science delivers sustainable solutions to advance mobility improve wellbeing and enhance modern life. Founded in 1928 Lubrizol owns and operates more than 100 manufacturing facilities sales and technical offices around the world and has about 8000 employees. For more information visit .

We value diversity in professional backgrounds and life experiences. By enabling a consistent unbiased and transparent recruitment process Lubrizol seeks to create a positive experience for candidates so we can get to know them at their best. We recognize unique work and life situations and offer flexibility ensuring our employees feel engaged and fulfilled in every aspect of life.

Join Our Thriving Team at Lubrizol as a Data Scientist/Statistician Intern (PhD level)

Unleash Your Potential. At Lubrizol were transforming the chemical industry and looking for exceptional talent to join us on this journey. If you are ready to join an international company with talent around the world and want to make a real impact we want you on our team.

What Youll Do:

The empowered and agile Data Science & Statistics team is charged with creating analytics systems that enable highly effective product development via virtual experimentation optimization and knowledge addition the team provides data science consulting services to the Lubrizol technical community throughout the world. Youll collaborate with a diverse group of passionate individuals to deliver sustainable solutions to advance mobility improve wellbeing and enhance modern life.

Potential projects (depending on intern skills and current Lubrizol needs):

  • Create predictive models by mining complex data for critical formulating or testing insights
  • Implement and assess algorithms in R and Python (SAS JMP or C#/C optional)
  • Research develop and operationalize new statistical machine learning and/or optimization methods
  • Implement and improve forecasting algorithms
  • Investigate applications of Cheminformatics modelling
  • Investigate active learning for process optimization
  • scheduling and inventory optimization
  • accelerate process and product development cycle using emerging AI methods (such as LLM RAG Agentic AI)

Previous intern projects include:

  • Predictive modeling using Bayesian and machine learning methods
  • R/Shiny tool development to enable model predictions and formulation optimization
  • Creation of an interactive visualization tool for monitoring predictive models
  • Development of a bootstrap procedure for a hypothesis test
  • Multitask learning (transfer learning) using co-regionalized Gaussian Processes
  • Multivariate variable selection approach using Variational Bayes
  • Multi-objective optimization using genetic algorithms
  • Survival modeling using bagged Cox proportional hazards regression trees
  • Bootstrap variance estimation for complex nonlinear models

What Were Looking For:

Requirements:

  • Enrolled in a PhD program such as statistics data science machine learning or in chemistry/chemical engineering with data science skills
  • Dual degree students (e.g. statistics/data science and chemistry chemical engineering computational chemistry etc.) are encouraged to apply

Skills That Make a Difference:

Our projects can be tailored to each interns individual skills and interests so candidates who are a good match for some of the skills listed are encouraged to apply even if they dont match every single one.

  • Significant coursework in one or more out of:
    • Predictive modeling
    • Bayesian approaches
    • Optimization
  • Able to efficiently manipulate process and analyse data of various modalities including numerical image text and beyond
  • Advanced programming skills and exposure to data query languages
  • Interest and experience in advanced statistical and machine learning methodology (PhD level)
  • Curiosity creativity initiative and autonomy

Perks and Rewards That Inspire:

  • Onsite at Hazelwood near Derby UK
  • Competitive hourly wage with tenure-based raises
  • Paid holidays within your work period
  • Subsidized on-site restaurant
  • Free car parking

Start and end dates are flexible dependent on your course structure and availability; internships typically last for 12-16 weeks.

Footer:

Ready for your next career step Apply today and lets shape the future together!

Its an exciting time to be part of is not staying put. We are continually learning and passion delivers our success not only for Lubrizol but for those who count on us every day: our employees customers and communities.

As a diverse global team we work together to solve some of the worlds most pressing challenges. We impact everyday lives through science only Lubrizol can deliver and we never stop pushing to do it better.

One of the founding principles of The Lubrizol Corporation more than 90 years ago was treating every employee with dignity and same commitment is only stronger than that we are committed to providing an environment where every employee can be the best they can be no matter their race colour religion sex national origin sexual orientation gender identity disability or protected veteran status or any other characteristic.


Required Experience:

Intern

Header: About LubrizolThe Lubrizol Corporation a Berkshire Hathaway company is a specialty chemical company whose science delivers sustainable solutions to advance mobility improve wellbeing and enhance modern life. Founded in 1928 Lubrizol owns and operates more than 100 manufacturing facilities sa...
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About Company

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As a leader in specialty chemicals, Lubrizol's mission is to be an essential ingredient in our customers' success. We are a market-driven, specialty chemical company with innovative technologies that include lubricant additives for engine oils and driveline fluids, industrial lubrica ... View more

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