Schlumberger is committed to create new drilling systems with a high degree of autonomy and intelligence to transform the sus
Research Scientist: Computer Science and Artificial Intelligence Planning
Schlumberger is committed to create new drilling systems with a high degree of autonomy and intelligence to transform the sustainability, efficiency and safety of constructing oil and gas wells. Accessing hydrocarbon reservoirs often involves drilling geometrically complex trajectories, through unpredictable and hazardous physical environments, to reach targets more than 10 km from the drilling rig. As part of our commitment to innovation and research, we are seeking research scientists to focus on the fundamental science and technology needed to create autonomous drilling systems that handle the complex physics and mechanics of the drilling process.
The successful candidate will form part of a multi-disciplinary team developing novel techniques of automated inference and decision-making, that integrate to form an autonomous drilling system. The candidate will contribute to the development of dynamic planning, as well as apply their experience in optimisation, efficient algorithm implementation, and knowledge systems to solve real-world problems. Successful Research Scientists investigate challenging questions, generate ideas, develop new solutions, and engage with business and engineering teams to ensure their solutions have a significant impact.
- Develop proof-of-concept solutions to real-world problems by investigating and applying Artificial Inteligence planning, optimisation and efficient algorithm implementation techniques Engage with business and engineering teams to turn proof-of-concept into engineered solutions
- Publish research papers, internal technical reports and patents, and present your work
- Learn about the oilfield domain
- Keep up to date and expand knowledge in your field of expertise
PhD degree in computer science, mathematics, or related fields (recent graduate)
- Expertise in automated AI planning, ideally with experience in PDDL domain modelling and knowledge engineering
- Competency in optimisation and knowledge systems
- Proficiency in algorithm development, programming, and software development
- Interest in application to real-world problems
- Strong teamwork and communication skills
The Schlumberger Cambridge Research Centre offers a stimulating research environment with real-world problems that push the limits of scientific knowledge. We are committed to be at the leading edge of science and to incorporate new emerging technologies in Schlumberger’s activities. To achieve that we recruit the most talented scientists from a variety of scientific and engineering backgrounds and give them opportunities to advance their fields of expertise as well as to develop solutions of significant industrial impact.
The Schlumberger Cambridge Research Centre strongly encourages the self-development of its scientists, offers high-end experimental facilities and scientific resources, and maintains strong collaborations with academic and industrial research groups worldwide.
Schlumberger is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law.