This position will work with the Computational Sciences Manager and will support molecular modelling for chemistry and materials science applications, focusing on electrochemistry, catalyst development, geochemistry, and general data science. This individual will work closely with a global team including Molecular Innovations Chemistry, Green Hydrogen, Subsurface Science, Materials Science, & Bioscience. Given the modelling supports across several areas of scientific expertise, in-person interaction is required. Strong communication, outstanding inter-disciplinary problem solving, and critical thinking skills are required, with a strong interest in the pursuit of scientific discovery.
Key accountabilities
- Serve as subject matter expert for molecular modelling and simulation methods with a focus on electrochemistry and catalysis. Develop capabilities and apply molecular modelling at multiple scales for applications in chemical and biological systems, and for developing new materials.
- Effectively communicate findings, insights, and advice to scientific and leadership teams, while working both independently and within multidisciplinary teams, supporting project work, academic programs, and industrial collaborations. Deliver quality scientific reports and presentations.
- Provide guidance on molecular modelling technology to experimentalists and due diligence of external parties/technologies. Provide strategic input on application of new technologies, including developments in molecular modelling for electrochemistry.
- Provide data science support through data integration and statistical analyses, including predictive machine learning (ML) and visualization.
- Promote safety initiatives and champion compliance with bp s Code of Conduct.
What do we want to see from you!
- Degree or equivalent experience in computational sciences, chemistry, chemical engineering, molecular modelling, quantum information science, physics, or related fields.
- Extensive experience with molecular modelling and associated methods including quantum mechanics (QM) with density functional theory (DFT), and molecular dynamics (MD) and Monte Carlo (MC) simulations. Application of methods for physical property prediction, multi-phase reaction characterization, and materials science (e.g., catalyst development).
- Experience in molecular modelling for electrochemistry, including for redox property predictions for electrochemical reactions, and characterization of electron transfer between multiple species including electrode and electrolyte materials and interfaces. Knowledge of structure optimization, free energy calculations, solvation effects, electrochemical material design, adsorption and electrode surface characterization.
- Extensive experience using innovative molecular modelling software (e.g., NWChem, QChem, Jaguar, VASP, LAMMPS, Desmond) using high-performance computing (e.g., Linux shell scripting).
- Consistent track record in applied Data Science for the development and application of algorithms in high-level programming languages (e.g., Python, R), ML/statistical tools (e.g., KNIME, JMP), and visualization (e.g., PowerBI).
Desirable criteria
- Knowledge of developing and applying ML predictive models for multivariate analyses, feature engineering, and molecular property predictive analyses (e.g., QSAR).
- Experience with molecular simulation approaches for biological or low carbon solutions, such as MD for bio-catalysis, and understanding of relevance in new technologies.
- Fundamental understanding on MD for subsurface science such as between adsorbents and natural porous systems, and chemical processes, including surface binding, diffusion, heat transfer, and absorption.
- Knowledge of emerging computing and modelling methods for computational chemistry, such as quantum computing, use of GPU, and machine learning interatomic potentials.
- Knowledge of process-scale multi-physics modelling (e.g., computational fluid dynamics).
- Proven track record to prioritise, coordinate and multitask in an agile and multidisciplinary environment, work independently, and effectively communicate to various audiences including senior management and technical teams.
