Geothermal Modeling Intern: Uncertainty Quantification

SLB; Cambridge; On-site; GBP 12,000 - 18,000; Full time

Job summary

SLB is seeking a Geothermal Research Intern (12 months) for a summer 2027 start at the Cambridge Research facility. The role focuses on uncertainty quantification in enhanced geothermal systems, using numerical modelling and statistics to study how input uncertainties affect reservoir-scale predictions.

The intern will compare models of different complexity and contribute to documentation, code preparation, and a final report identifying valuable measurements or modelling approaches.

Qualifications

• Studying for a Bachelor or Master in Applied Mathematics, Computer Science, Physics, Engineering, Geosciences or related field.
• Foundation in numerical methods, probability and statistics.
• Programming in Python or similar language.
• Ability to analyse data and explain results clearly.

Responsibilities

• Review measurement options and modelling approaches relevant to the selected case study.
• Carry out a computational study to quantify prediction uncertainty.
• Compare predictions from models of different complexity with observations.
• Prepare documented code and a report recommending where additional measurements or more detailed modelling would be most useful.

Skills

Python

Numerical methods

Statistics

Data analysis

Education

Bachelor's/Master's in a relevant field

Tools

Python

Job description

SLB is seeking a Geothermal Research Intern (12 months) for a summer 2027 start at the Cambridge Research facility. The role focuses on uncertainty quantification in enhanced geothermal systems, using numerical modelling and statistics to study how input uncertainties affect reservoir-scale predictions.

The intern will compare models of different complexity and contribute to documentation, code preparation, and a final report identifying valuable measurements or modelling approaches.