PostDoc - Electron Correlation Measures and Diagnostics (Closed)

Strongly correlated or multireference (MR) systems, require adequate electronic structure methods, which must be chosen according to the results of MR diagnostics. To date, MR measures and diagnostic tools have largely been limited to gas-phase calculations. However, such correlation measures are equally needed in the solid state, where a reliable MR diagnostic remains unavailable. This project also aims to fill this gap, providing MR diagnostic tools that can be applied across a broad range of systems while utilizing minimal computational resources.

Additionally, we aim to train a machine learning model using a NOO dataset capable of predicting MR character from Kohn-Sham or semi-empirical orbital occupancies, or even simpler information obtained from molecular representation formats. This approach will significantly reduce computational costs, ultimately becoming an MR diagnostic tool suitable for high-throughput computational screening.

The candidate should have a strong background in computational chemistry, and experience in strongly correlated methods. Programming skills, solid knowledge of various computational packages will be highly appreciated. They must have a bachelor in chemistry or physics and a PhD in computational chemistry or molecular physics. Other merits related to the project description will be also valued.

• Estimated annual gross salary: Salary is commensurate with qualifications and consistent with our pay scales
• Target start date: 2025/04/01

We provide a highly stimulating research environment, and unique professional career development opportunities.

We offer and promote a diverse and inclusive environment and welcomes applicants regardless of age, disability, gender, nationality, ethnicity, religion, sexual orientation or gender identity.

The project will be supervised by Dr. Eduard Matito, head of the quantum chemistry development group (https://quantchemdev.github.io) in collaboration with Dr. Eloy Ramos-Cordoba from CSIC (Barcelona).

Interested candidates should submit an updated CV and a brief statement of interest to the following application email below. 

Reference letters are welcome but not indispensable.

The reference of the specific opening to which the candidate is applying should be stated in the subject line, and the application must be received before the application deadline.

Although candidates are welcome to contact the project supervisors to know further details about the proposed research activity, please be aware that the application will be evaluated only if it is submitted directly to the email address listed below as application email.

• Reference: 2024/37
• Application deadline: 2024/10/21
• Application email: jobs.research@dipc.org

Applications received by the deadline will be evaluated by a Committee designed by the DIPC board on the basis of the following criteria:

• CV of the candidate (40%)
• Adequacy of the candidate’s scientific background to the project (40%)
• Reference letters (10%)
• Other: Diversity in gender, race, nationality, etc. (10%)

Evaluation results will be communicated to the candidates soon after. Positions will only be filled if qualified candidates are found.

The DIPC may revoke its decision if the candidate fails to join by the appointed time, in which case the position will be awarded to the candidate with the next highest score, provided it is above 50 (out of 100).

However, the selected candidate may keep the position if, in the opinion of the Selection Committee, the candidate duly justifies the reasons why he or she cannot join before the specified deadline, and as long as the project allows it.

This project has received funding from the Spanish Government’s grant program “Proyectos de Generación de Conocimiento 2022” under grant number PID2022-140666NB-C21, MCIN /AEI /10.13039/501100011033 / FEDER, UE.