Computational Scientist, Formulation and Materials Modeling, at ExxonMobil, Bengaluru
Job Description
This computational scientist job in Bangalore is with ExxonMobil. You will build hybrid models that mix chemistry and materials science with machine learning. The models predict how a product’s formulation and processing affect its performance, so R&D teams can develop products faster.
At a glance
- Position: Computational Scientist (full time, job 1435638000)
- Where: Bengaluru, India
- Degree: PhD or Master’s in Chemical Engineering, Materials Science, Mechanical Engineering, Data Science or a related field
- Experience: Master’s candidates need 3+ years in industry
- Posted: 1 October 2026
- Apply: 31 December 2026 (the end date on the posting)
What the computational scientist does
- Develop hybrid models that combine first-principles chemistry and materials knowledge with data-driven methods
- Analyse lab, pilot and field data to link formulation and processing conditions to product performance
- Build predictive models for formulation optimisation, performance, product stability and quality
- Design experiments (DOE) to generate data for building and checking models
- Check models with proper validation and uncertainty quantification
- Work with R&D scientists, chemists and product developers, and build reusable modelling tools
Why this role matters
Testing every new formulation in the lab is slow and costly. Models that combine physics and data cut the number of experiments needed. This role suits a chemical engineer or materials scientist who already uses machine learning in research.
What ExxonMobil is looking for
- PhD or Master’s in Chemical Engineering, Materials Science, Mechanical Engineering, Data Science or a related field
- Master’s candidates need at least 3 years of industry experience
- A strong foundation in hybrid modelling: domain knowledge plus statistical and machine learning methods
- Experience using models for product development, formulation optimisation and performance prediction
- Python or another language for data analysis, modelling and automation
- Experience with time-series and experimental data on product performance, stability and quality
Nice to have
- Experience in downstream, chemical, or materials and product development settings (strongly preferred for Master’s candidates)
- Formulation modelling or property prediction
- SQL and data platforms such as Databricks, Azure, AWS or Snowflake
Pay and location
The posting does not state pay. ExxonMobil lists benefits including medical plans, retirement benefits, day care assistance, tuition assistance and a relocation programme. The posting’s end date is 31 December 2026.
How to apply
Apply through the official ExxonMobil page. The closing date is 31 December 2026 (the end date on the posting).
See all our industry R&D jobs, or browse more research jobs on ResearchJobs.in.
Hiring institution: ExxonMobil
Official advertisement: jobs.exxonmobil.com
How to prepare for this application
- Prepare one project where you combined a physical model with machine learning, and show how it beat either alone
- Revise design of experiments: factorial and response-surface designs, and how you pick runs for a new formulation
- Be ready to explain how you quantify uncertainty in a model's predictions, for example with Gaussian processes or ensembles
- Think through a product stability problem: what data you would collect and which features you would build
- Bring a clean Python example and explain how you made the workflow reproducible
About ExxonMobil
ExxonMobil is a US energy and chemical company. It produces oil, gas, fuels, lubricants and chemicals. Its Bengaluru technology centre supports research, engineering and digital work for its global businesses.
