Job announcements relevant to people interested in electronic structure calculations…
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.
Two-year post-doc position on machine-learned in ... (No replies)
Back to Job listings...
We offer a two-year postdoc position at the Department of Physics of the University of Trieste, Italy. The postdoc will work under the supervision of Maria Peressi and Antimo Marrazzo on the development and application of interatomic potentials based on deep neural networks to study complex phenomena in 2D and van der Waals materials at finite temperature.
Possible applications will range from the simulation of phase transitions, charge density waves, anharmonic phenomena, to the study of monolayer-substrate interactions, moiré patterns, growth processes and catalysis. In addition, we are also interested in the study of dynamical spin-orbit coupling effects, especially for spintronics and topological materials.
Beyond application-oriented studies, the position also involves the development of robust protocols and automated AiiDA workflows for constructing machine-learned potentials with state-of-the-art techniques based on active learning and Bayesian inference, including the generation and dissemination of ab initio simulations databases and models based on equivariant deep neural networks.
The contract is for two years, starting in the first half of 2023.
The city of Trieste has the highest density of researchers per population in Europe (37 every 1000 inhabitants). Trieste has a particularly strong tradition in electronic structure theory and simulations, which is fostered by the University of Trieste and other research institutions such as ICTP, SISSA and the Materials Foundry of the National Research Council (CNR-IOM). The close proximity of several research institutions facilitates scientific exchange and collaborative work not only among theorists but also with leading experimental groups at the local synchrotron (ELETTRA), free-electron laser (FERMI) and materials foundry (CNR-IOM).
Candidates are sought with passion and commitment to the field and with strong motivation and commensurate academic record. Expertise in the development and application of first-principles techniques is required. The ideal candidate has a robust and documented expertise in the use of electronic-structure simulation software (e.g. Quantum ESPRESSO) and classical molecular dynamics (e.g. LAMMPS), including the exploitation of HPC infrastructures and materials’ informatics (e.g. AiiDA). Previous experience with machine learning methods is considered a plus.
Expression of interest
We strongly encourage interested candidates to send an expression of interest to [email protected]. Applicants should include:
- a detailed CV containing a list of publications and a detailed description of both scientific and computational background,
- motivation letter (max 1 page)
- name and email address of at least two people who might be contacted for a reference letter.
The deadline for expressions of interest is *15 December 2022*.
Funding & Salary
The position is funded by the Spoke Materials and Molecular Sciences of the newborn National Centre for HPC, Big Data and Quantum Computing, which is financed by the European Union program NextGeneration EU. The net salary is about 1600 EUR/month, which is compatible with a good living standard. The cost of living and real estate in Trieste is moderate and the quality of life excellent.
The city is medium size and beautifully located at the most northerly spot of the Adriatic Sea. Local social life is lively, with cultural and natural attractions (theatres, sports, nightlife, the Karst highland, Venice, the Alps, and beautiful seaside resorts) a few strides to one hundred miles from the center of the city. Trieste is also an international sailing capital, hosting every year the world’s largest regatta and regularly producing top Olympic sailing athletes.