As a resident you will join our computational scientists, data scientists and AI engineers to solve real business issues using huge pools of data throughout the many businesses within Shell.

The programme is hosted and organized by Shell’s Digital Centre of Expertise, part of Shell’s Technology business unit which offers the opportunity to lead the transformation of an industry. We are looking for people with a passion for developing solutions with potential of unlocking more and cleaner energy. The Programme offers Residents the opportunity to collaborate with like-minded innovators, experts and mentors, while deepening technical expertise across the spectrum of AI.

Artificial Intelligence

Artificial Intelligence

From machine learning to computer vision, reinforcement learning to virtual assistants, and autonomous vehicles to robotics, Shell has been focused on a range of technologies that have supported advances in AI. Foundational methodologies such as numerical optimization, statistics, and fusion of observed data with underlying physics are given equal importance. Businesses that harness new data sources and use AI and machine-learning technology to provide insights will be in a strong position to shape future commercial development and influence how society changes. A steep rise in the number of connected devices and an explosion in data volumes are already delivering unparalleled levels of business disruption. The recent explosion in data volumes and availability has led to a step change in the training of algorithms and provided important new insights: easy access to vast data volumes is making AI algorithms smarter.

The AI group is spread across four international locations and collaborates with universities and national research laboratories in India, UK, The Netherlands, and the USA.

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Computational Science

Computational Science

Computational Science uses physics-based models to predict the behaviour of materials and systems using high performance computing. Computational science augments traditional research methods by accelerating and guiding experimental work and providing insight into processes and results. It is used across Shell’s businesses to predict everything from the chemistry of catalysts and batteries to capturing flow through reactors, pipelines and rocks. These are complex simulations which require high performance computing and algorithm optimisation.

The Computational Science Centre of Excellence is based in Bangalore, India, but the team includes staff in Amsterdam, the Netherlands, and Houston, USA. Computational science is a broad discipline. Within Shell, it draws on expertise from more than 50 technologists in disciplines such as chemistry, physics, mathematics, material science and mechanical, chemical, aerospace and metallurgical engineering. This team has strong external links and collaborates with high-profile global companies, technology start-ups and leading academic institutions. 

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AI Engineering

AI Engineering

AI Engineering is a hybrid skillset covering data engineering and data science related concepts in wider spectrum of AI paradigms such as predictive analytics, natural language processing, machine learning, machine vision, deep learning, hyper-personalisation, computer-aided decision-making, human/computer interaction, autonomous systems, goal-driven systems, patterns & anomaly detection.

The AI Engineering team is part of the Data Science Centre of Excellence, and has team members based in Bangalore, India as well as Amsterdam, The Netherlands, London, UK and Houston, USA. Within Shell, AI Engineering draws expertise from more than 50 technologists in disciplines such as machine learning frameworks, cloud tech, edge computing, distributed computing, software development, with examples including but not limited to: Javascript, Pytorch, Kubernetes, Docker, KubeFlow, C#, Python, Tensorflow ; Shell’s data science COE has strong external links and collaborates with high-profile global companies, technology start-ups and leading academic institutions. Hackathon for Sustainable and Affordable Energy

Around 5000 contestants signed up to compete in the Windfarm Layout Optimisation coding challenge. 14 teams made the finalist shortlist and 8 emerged as the winning teams.

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