Research Scientist
SLBAbout the role
We are seeking a Research Scientist to join our exceptional team at Schlumberger Doll Research (SDR) in Cambridge, Massachusetts—a place where pioneering science drives real‑world innovation. Schlumberger-Doll Research (SDR) conducts both fundamental and applied research to develop innovative technologies for the energy industry. Our teams are building the next generation of multi‑physics software and hardware systems designed to probe deeper and more accurately understand energy resources. This work leverages advanced data-generating models, state-of-the-art AI/ML algorithms, extensive domain expertise, and robust cloud computing infrastructure available within SDR and across SLB globally.
Role Overview
As a Research Scientist, you will collaborate closely with scientists and subject-matter experts to design and implement advanced computational and algorithmic models for next-generation probing technologies. This includes developing physics-informed, data-driven interpretation frameworks and working with cutting-edge modeling tools to solve complex, data-intensive challenges.
Key Responsibilities
- Design and develop computational models for electromagnetic and multi-physics applications
- Build physics-informed and data-driven algorithms for interpretation of complex, multi-dimensional signals
- Collaborate across multidisciplinary teams to integrate domain expertise into modeling frameworks
- Analyze large datasets to extract actionable insights
- Contribute to forward-looking research exploring next-generation technologies (e.g., quantum computing, space-related applications, advanced sensing)
Required Qualifications
- PhD in Electrical Engineering, Computational Physics, Electromagnetics, or a related field with relevant domain specialization
- Strong background in computational physics, with a preference for electromagnetics
- Vision and interest in advancing next-generation scientific and technological applications
Preferred Qualifications (Optional)
- Knowledge of inversion or optimization algorithms
- Experience with AI/ML frameworks, deep learning, or statistical modeling
- Experience in computational modeling and simulation
- Experience with finite element analysis tools (e.g., COMSOL, NGSolve, Ansys)
- Software development skills
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, a 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.
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When certifying your application, you are also certifying on reading and understanding all of the below supplemental information. For purposes of the application and the below information, Company shall be defined to mean SLB. Please note that the below supplemental information and the employment application are NOT a contract.
- 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.<
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