Job announcements relevant to people interested in electronic structure calculations…
Due to the large number of posts recently, there is currently a delay of several weeks between posts being submitted and the corresponding emails being distributed to all users. Please bear with us while we try to improve this. In the meantime – and until this notice is removed – it would assist us considerably if you could submit only important and/or urgent posts and thus help to reduce the size of the mail queue. Under no circumstances should you resend posts multiple times when you find the emails are not distributed immediately.
In light of the Russian military offensive in Ukraine, we request that announcements relating to events, jobs and other activities associated with institutions supported by the Russian and Belarusian states are not posted to the Psi-k forum.
Postdoctoral position in ab initio simulated spe ... (No replies)
Back to Job listings...
The Nanoscience Institute of the National Research Council (CNR-NANO) is looking for a postdoctoral candidate working in the field of ab initio modelling of materials and interfacial processes in battery materials, including simulation of spectroscopic features by exploiting machine learning approaches for direct comparison with experimental results. The research activity builds in the context of the European BIG-MAP project (Battery Interface Genome – Materials Acceleration Platform, http://www.big-map.eu), under the long-term Battery2030+ initiative.
Research group: The postdoctoral fellows will work at the S3 Center of the Nanoscience Institute of CNR (Modena, Italy), under the supervision of: prof. Elisa Molinari and Dr. Deborah Prezzi. Further info on the personal webpages at: http://www.nano.cnr.it/?mod=men&id=102. Moreover, they will benefit from the connection with, and the lively environment fostered by the MaX Centre of Excellence for Materials design at the eXascale (www.max-centre.eu), including support for the usage of MaX flagship codes.
Candidate profile: Successful applicants should hold a Ph.D. in computational or theoretical physics / chemistry / materials science, with a solid background in modelling structural and electronic properties of materials with state-of-the-art ab-initio methods, high-performance computing, implementation of software and automated workflows. Prior experience in the modelling of energy materials and/or simulation of spectroscopic features and/or in the exploitation of machine learning approaches will be evaluated as preferential titles. Very good oral and written proficiency in English is compulsory.
Duration: starting with a 1-year appointment, renewable upon mutual agreement
Information and application: For information on how to apply, please write to [email protected] providing: (i) curriculum vitae (including research interests and accomplishments & full publications list) and (ii) full contact details of two referees supporting the application. Selected candidates will be interviewed via telecon.
Deadline for application: 29 Sept 2022.