Electronic Structure and machine learning protocols for pre-screening of near-room temperature spin-crossover materials

Application deadline:

A 3-year doctoral fellowship is available in the field of computational modeling of spin-crossover (SCO) processes in transition metal based systems of different complexity, ranging from molecules to materials. These materials can operate as molecular level switches, thus making them promising candidates for nanoscale memory devices and sensing applications, among others. The proposed project involves the use of different electronic structure methodologies, as well as novel computational protocols, such as machine learning techniques, in order to identify the factors that control SCO behavior, thereby enabling a rational design and an accelerated discovery of new SCO materials with tailored properties.