Senior Research Scientist
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About The Position
The position involves researching, benchmarking, and adapting state-of-the-art AI-based models on real field measurements for various applications such as anomaly detection, event recognition, and inference. The role requires extracting critical business insights using advanced data analytics on large-scale databases containing multi-modal field measurements. Responsibilities include designing and optimizing algorithms for efficient downhole data compression and inference at the edge, developing hybrid models that merge predictive insights from data-driven approaches with physics-driven mechanical models, and engineering smart sensor fusion frameworks for effective parameter estimation with uncertainty quantification. Additionally, the position involves orchestrating and optimizing MLOps workflows to streamline the training, validation, deployment, and monitoring of machine learning models, designing and integrating robotic systems to enhance operational efficiency through automation, and developing solutions for Bayesian state estimation, uncertainty quantification, path planning, and robotics control. The candidate will also lead the adoption of AI-based algorithms to improve robustness and scalability, collaborate and mentor interns and contractors, and present technical talks at conferences and symposia.
