About this role
Job Summary As a Senior Postdoctoral Scholar, you are expected to establish a computational pipeline to achieve catalyst prediction for CO2 electrocatalytic reduction reactions. This is a multi-step approach, where first DFT will be used to understand reactions, then explore the use of machine learning potentials towards kinetic and large length scale/time scale simulations and eventually integrate into the experimental workflow. You will be based in at the BEARS Consortium in Singapore at CREATE and will work in a highly collaborative environment as part of the AxCIS team in Singapore, addressing challenges at the interface of materials chemistry, high-throughput synthesis, artificial intelligence, and robotic automation. Duties & Responsibilities: • Perform electronic structure calculations on bulk, surfaces, nanostructures as necessary. • Develop AI/ML models to predict materials reactions using data-driven approach. • Develop codes as necessary to assist existing and new code frameworks for advanced property prediction and analysis. • Analyze and present results in meetings or conferences. • Disseminate research outputs through high-impact publications, presentations, and data releases in accordance with open science practices. • Collaborate with experimental team members, including partners in academia, industry, and national laboratories. • Mentorship of junior team members, which can include undergraduate and graduate students. Qualifications: • PhD in a relevant discipline (e.g. Chemistry, Materials Science and Chemical Engineering). Other Desired Qualifications / Experiences / Skills: • >5 years Post-PhD experience • Expertise in Artificial Intelligence/Machine Learning models • Expertise in density functional theory calculations for catalysis applications
Also in Data Science
NO DEVIATION PTE. LTD.
PERCEPT SOLUTIONS PTE. LTD.
OUTSOURCE NOW PTE. LTD.