Where you fit
Shell’s Projects and Technology (P&T) business exists to make the delivery of our strategies and the growth of our company possible. Our team develops the advanced products and technologies Shell needs to meet customer demand. Our solutions help our partners grow the LNG, Gas and Power businesses, deepen the integration of Manufacturing, Chemicals and Trading, and maximise the competitiveness of our Upstream business.
What’s the role?
As an AI Resident - Material Informatics, you’ll be helping Shell build an enabling computational capability in supporting businesses and strategies of Shell. Your role will focus on building capabilities and skills in Material informatics to solve targeted problems in Shell's traditional businesses and new areas related to energy transition.
You will develop and use sophisticated data mining, data analytics and machine learning based approaches in conjunction with materials knowledge coming in from multiscale materials modeling and experiments to establish processing-structure-property-performance (PSPP) relationships in materials towards accelerated materials selection/discovery/development. You will develop/apply methods/tools to identify patterns/features and extract the maximum possible information from high-throughput simulations, experiments and databases (e.g. from analytical characterization data, process data, sensor data etc.).
In addition to the above we want you to critically test ideas through the "fastest route to failure" and/or to champion & develop such technologies to the point of organizational commitment.
Open Innovation (selection, initializing, and effectively utilizing external technical collaborations in Asia, Europe and the Americas) is an important element of the job scope, as is dissemination of findings via reputed international conferences & reports/publications.
What we need from you
We are keen to hear from candidates with a research aptitude and original thinking. We expect her/him to be capable of business problem solving, with a mindset to deliver end-to-end technical solutions, have flexibility and technical breadth in learning and applying appropriate tools (different machine learning algorithms and computational techniques as required for solving material science and engineering problems).
Of course, you’ll need to convince us that you have a keen interest in Shell’s core technologies like catalysis, chemicals etc. but also new technologies of interest such as electrocatalysis, direct air capture, electrification, hydrogen etc. You should have competencies to evaluate, discover or invent new computational approaches relevant to above mentioned areas. Experience in R&D in early parts (TRL 1-5) of the R&D funnel. You should have a proven track record of delivery via deployment, dissemination of knowledge via reports and external publications. For you to be able to quickly grasp technical detail and to work directly with experts (both experimental, computational) in these fields, it’s vital that you have the all-round communication skills. You should be able to translate that information into language that’s readily understood by non-technical clients and colleagues from other backgrounds.
Beyond that, we’d like to see the following on your CV:
- At least a Master’s or PhD specializing in material informatics and one or more multi-scale simulation technique(s) from any of the disciplines in Materials Science, Physics, Chemistry, Mechanical engineering, Metallurgical Engineering or any other allied fields with related qualification.
- Experience of minimum 2 years years hands-on post-doctoral or industrial R&D experience in Computational Materials Science focusing on material informatics with a strong statistics and mathematics foundation. More year’s required if Master’s degree holder.
Material Informatics; data analytics; data mining; Computational Materials Science; machine learning