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.

Postdoc position (No replies)

pavanell

3 months ago

pavanell 3 months ago

The Pavanello Research Group at Rutgers University-Newark seeks applicants for a Postdoctoral Associate position to start in the summer 2024. We seek applicants who have strong skills in software development and who are comfortable with electronic structure theory (DFT, wavefunction methods). The appointment is initially for one year with the possibility of renewal upon mutual agreement and satisfactory performance. Visit here to apply, or send inquiries directly to Michele Pavanello at [email protected]

 

The Pavanello group develops electronic structure methods based on orbital-free DFT, density embedding and machine learning. For each of these avenues of research, we consider ground electronic states as well as states out of equilibrium. The successful candidate will develop novel electronic structure methods based on density embedding (including 1- and 2-rdm  embedding) exploiting surrogate electronic structure solvers based on machine learning (see for example our recent paper).

 

Interested candidates can consult the Pavanello group website, publication list and software stack:

DFTpy: orbital-free DFT/TD-DFT

QEpy: Quantum ESPRESSO in python

eQE and eDFTpy: density embedding / subsystem DFT

QMLearn: quantum machine learning (see also qmlearn.rutgers.edu)