Scientific Computing Researcher

SLB; Cambridge (MA); On-site; USD 105,000 - 214,000; Full time

Job summary

Schlumberger-Doll Research (SDR), SLB's global research and innovation center in Cambridge, MA, seeks a Scientific Computing Researcher to join a multidisciplinary team of scientists. This role focuses on developing next-generation computational solutions for subsurface characterization and energy challenges.

You will collaborate with geoscience, reservoir engineering, data science, and software development teams to advance physics-informed methods and AI.

Qualifications

• Master's degree or PhD in Applied Mathematics, Computational Science, Physics, Engineering, or related quantitative discipline.
• Strong foundation in applied mathematics, uncertainty quantification, statistical inference, signal processing, and data analysis.
• Proficiency in scientific programming using Python/C/C++, with associated scientific computing libraries.
• Experience applying mathematical or computational methods to physical science problems.

Responsibilities

• Partner with researchers to identify and develop technical solutions for real-world challenges.
• Develop, test, and benchmark algorithms grounded in physical principles to interpret measurements and infer subsurface properties.
• Assess the quality, reliability, and uncertainty of measurements and inversion-derived results.
• Identify opportunities to improve estimation accuracy through the integration of multiple physics domains and data sources.
• Design and develop prototype solutions for validation, deployment, and transfer to engineering teams.
• Collaborate with multidisciplinary teams across geoscience, reservoir engineering, formation evaluation, data science, and software development.
• Investigate and develop agentic AI solutions to assist data acquisition engineers in the planning and execution of field operations.
• Publish research findings in leading scientific journals and present results at internal and external technical forums.
• Support the transition of research innovations into practical applications and operational deployment.

Skills

Python

C/C++

Machine learning

Uncertainty quantification

Data analysis

Scientific computing

Education

Master's degree or PhD in Applied Mathematics, Computational Science, Physics, Engineering, or related quantitative discipline

Tools

NumPy/SciPy

SciPy stack

Job description

Schlumberger-Doll Research (SDR), SLB's global research and innovation center, is seeking a Scientific Computing Researcher to join a multidisciplinary team of scientists in Cambridge, Massachusetts, adjacent to the MIT campus.

This is an exciting opportunity to contribute to breakthrough research with direct impact on some of the world's most pressing energy challenges. Working at the intersection of science, engineering, and advanced computing, you will help develop next-generation solutions that enable cleaner, more efficient, and more sustainable energy systems.

The position is part of the Geosciences Department and focuses on advancing our capabilities in developing innovative computational solutions that enhance our understanding of geological systems, maximize the value of physical measurements, and improve operational efficiency in the characterization and management of subsurface assets.

Key Responsibilities

• Partner with researchers, engineers, and domain experts to identify and develop technical solutions for real-world challenges.
• Develop, test, and benchmark algorithms grounded in physical principles to interpret measurements and infer subsurface properties.
• Assess the quality, reliability, and uncertainty of measurements and inversion-derived results.
• Identify opportunities to improve estimation accuracy through the integration of multiple physics domains and data sources.
• Design and develop prototype solutions for validation, deployment, and transfer to engineering teams.
• Collaborate with multidisciplinary teams across geoscience, reservoir engineering, formation evaluation, data science, and software development.
• Investigate and develop agentic AI solutions to assist data acquisition engineers in the planning and execution of field operations.
• Publish research findings in leading scientific journals and present results at internal and external technical forums.
• Support the transition of research innovations into practical applications and operational deployment.

Desired Skills And Qualifications

• Master's degree or PhD in Applied Mathematics, Computational Science, Physics, Engineering, or a related quantitative discipline.
• Strong foundation in applied mathematics, uncertainty quantification, statistical inference, signal processing, and data analysis.
• Demonstrated experience applying mathematical or computational methods to solve problems in one or more physical science domains.
• Proficiency in scientific programming using languages such as Python, C, or C++, along with associated scientific computing libraries.
• Experience with machine learning and artificial intelligence methods; exposure to agentic AI frameworks and applications is highly desirable.
• Strong analytical thinking and problem-solving capabilities.
• Ability to work effectively in a multicultural and multidisciplinary research environment.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Experience developing physics-informed or hybrid physics-AI solutions.
• Familiarity with inverse problems, optimization methods, and uncertainty quantification techniques.
• Experience working with geoscience, energy, or subsurface-related applications.
• Track record of scientific publications, technical presentations, or applied research contributions.

The compensation and benefits for this role are listed in compliance with applicable law. We are committed to offering fair and competitive pay aligned with each candidate’s skills, experience, and qualifications, within the designated salary range for the role. Please note that the listed compensation and benefits apply only to successful candidates hired onto a local United States payroll. The anticipated annual salary range for this position is $105,280 - $213,800. SLB offers a comprehensive total rewards package, which includes variable pay, health care coverage, retirement plan, protection programs, paid time off, and various training opportunities.

ALL APPLICANTS FOR U.S. ROLES MUST CAREFULLY READ ALL THE SUPPLEMENTAL U.S. SPECIFIC INFORMATION LISTED BELOW

• EQUAL EMPLOYMENT OPPORTUNITY & VETERANS Company policy is to provide every individual a fair and equal opportunity to seek employment and advancement at the Company without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, citizenship, genetic information, veteran or military status, disability, creed, ancestry, pregnancy (including pregnancy, childbirth and related medical conditions), marital status or any factors protected by federal, state, or local laws. We are an "Equal Opportunity Employer". For more information please, refer to the latest version of "Know Your Rights" poster and the "Pay Transparency Nondiscrimination Poster" located here: https://www.dol.gov/agencies/ofccp/posters. The Company is a VEVRAA Federal Contractor - priority referral Protected Veterans requested.
• REASONABLE ACCOMMODATIONS The Company will endeavour to make a reasonable accommodation / modification to the known physical or mental limitations of a qualified applicant with a disability to assist in the hiring process, unless the accommodation would impose an undue hardship on the operation of our business, in accordance with applicable federal, state, and local law. If you believe you require such assistance to complete the application or to participate in the interview process, please contact [e-mail] to request assistance. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to.
• AUTHORIZATION FOR EMPLOYMENT Pursuant to the Immigration Reform and Control Act of 1986, all applicants who are offered and accept employment must produce documents establishing their identity and authorization for employment in the United States. These documents must be produced no later than seventy-two (72) hours after employment commences. In addition, all applicants who are offered and accept employment will be required to verify their employment authorization under oath by signing a USCIS Form I-9. SLB is an E-Verify employer.