Engineer – Mechanical – Smart-Apps Global R&D Engineer
Under general supervision, the Global R&D engineer will be tasked to develop smart applications for our real-time platform, the EDGE. These applications are expected to cover multiple aspects of the well construction process and to leverage the low-latency, high frequency data and two-way communication with the rig control and operating systems.
The Global R&D Engineer will be focusing on processing and analyzing the real-time data to identify models parameters and events such as kicks, loss circulations, rig states, pick-up and slack-off procedures, as well as abnormal values in the stand pipe pressure. When needed, the Global R&D Engineer is expected to develop and expand the underlying physics-based models to capture better the phenomenology of the drilling system. These algorithms and events will be correlated to best practices and smart tools and visualization for the end users (drillers, company men, drilling engineers).
The Global R&D Engineer will be involved in all steps of the design process, from scientific proves of concept to field testing and validation.
Develop smart applications for the EDGE platform around well construction.
Leverage real-time, low-latency data for system identification and calibration as well as for the detection of dysfunctions or specific events.
Provide scientific judgement on developing fit-for-purpose models, combining theoretical principles and empirical trends.
Collaborate with the stakeholders (product owner, software team, data-science team) to deliver applications that add value for our internal and external customers.
Present results of analyses, including assumptions, equations, limitations, and validation of the applications and mathematical models.
Keep up to date with latest technical advancements in relevant fields.
Skills acquired through the completion of a master’s degree and two years of related experience or a Ph.D. in a quantitative field (mechanical or aerospace engineering preferred). Familiarity with the well-construction process is a plus.
Strong knowledge and experience in system identification, optimization, and estimation techniques for complex systems.
Demonstrated experience in translating phenomena into first-principle mathematical models.
Experience writing code in Python. R and Spark are a plus.
Knowledge and practical experience in data analytics, including machine learning techniques such as SVM, neural networks, Bayesian networks, random forests…
Experience with real-time implementation and validation of applications or prototypes.
Demonstrated teamwork, strong communication and analytical skills, and collaborative in complex engineering projects.
Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher-level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs. Depending on education, experience, and skills a variety of job opportunities might be available including, R&D Senior Engineer or R&D Principal Engineer.
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