We are looking for candidates with an excellent research record and with educational competence within the field of Computational Chemistry or related areas to perform research on properties of chemicals and polymers, as well as catalyzed chemical transformations. The job will require the consideration of a broad range of applications including thermal, catalytic and electrochemical reactions, and dynamic property prediction at the atomistic level ranging from single molecule, to mixtures, to periodic materials and surface and interfacial chemistries. It is also important to know how to build relationships between the atomistic simulations and macroscopic properties of materials and reaction processes, while collaborating with experimentalists. The job will be focused on the application of computational chemistry (i.e., electronic structure theory, statistical mechanics, atomistic Monte Carlo and molecular dynamics) to a range of chemicals and reactive materials (e.g. metallocene catalysts, zeolites, metal nanoparticles, olefin polymerization).
What you will do
You will use computational chemistry methods to simulate and predict properties and chemical transformations for chemicals and polymers, including, but not limited to catalysis, kinetics, adsorption, and reactions involved in the manufacturing process
You must be able to work independently, but closely with experimental chemists, materials scientists, characterization scientists, data scientists, and engineers to identify, adapt, develop, and deploy methods that bring commercial success to new products and processes
The successful candidate will also know how to integrate traditional physics-based methods with data-driven methods (e.g., Machine Learning) to address these challenges to achieve actionable in-silico predictions.
About you
Skills & Qualification:
PhD in chemistry, chemical engineering, computational chemistry, physics, computational physics, or a related degree
At least 3 years of computational chemistry research experience (including PhD research)
Extensive expertise and experience with computation of chemical properties and reactions using electronic structure theory (e.g. density functional theory), Monte Carlo, and molecular dynamics, as well as corresponding modeling software packages
Expertise in transition state theory, kinetics
Experience with high performance computing and massively parallel computer systems
Significant coding experience, preferably with fluency in Python or other scripting languages for automation and C++
Solid background in catalysis, hydrocarbon chemistry, polymers, carbon materials, and the chemical processes for their manufacture
Ability to propose, implement, and lead new approaches to accelerate chemicals and catalysis discovery and development
Excellent communication with strong ability to develop partnerships and relationships across functional areas, and strong collaboration skills with experimentalists
Experience with developing and deploying computational tools to support experimental efforts, and ability to convince users to utilize new tools and facilitate their implementation.
Preferred Qualification/ experience
Statistical mechanics and thermodynamics (i.e., equations of state)