Duties
The PhD student will engage in a research project that concerns materials modeling of electrified solid-liquid interfaces for energy storage. We will explore the finite-field molecular dynamics which we developed recently, see the review of the method J. Phys.: Energy, 2020, 2: 032005. This will be combined with our new efforts on the development of atomistic machine learning, see J. Chem. Inf. Model., 2020, 60: 1184. The project will focus on the application of these new techniques in studying metal-oxide/electrolyte interfaces. This PhD project is financed by the European Research Council (ERC).

Requirements

• The candidate should have a Master's degree in chemistry (or related disciplines), and possess a good understanding of physical chemistry and materials chemistry or
• has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle, or has acquired essentially equivalent knowledge in some other way in Sweden or abroad.
• The candidate must have excellent capabilities in written and oral English.

Additional qualifications

• Previous experiences with molecular dynamics simulations and (periodic) quantum chemical calculations are highly desirable.
• Familiarity with atomistic machine learning will be a plus.

About the employment

Scope of employment 100 %. Starting date 2022-09-01 or as agreed. Placement: Uppsala

For further information about the position, please contact:  Dr. Chao Zhang ([email protected] and +4618-471 3721)

Please submit your application by 2022-03-31 through the following link:

https://uu.varbi.com/what:job/jobID:476883/