Automated Interactive Infrastructure and Database for Computational Science

If you use AiiDA please cite:
AiiDA 1.x
Main paper: S.P. Huber et al., Scientific Data 7, 300 (2020)
AiiDA engine: M. Uhrin et al., Comp. Mat. Sci. 187 (2021)

AiiDA 0.x
First paper, ADES model: G. Pizzi et al. Comp. Mat. Sci. 111, 218-230 (2016) (open access version)


Two doctoral/postdoctoral positions in 1) high-throughput materials discovery, 2) HPC/HTC/HPDA software engineering

👤 🕔 October 25, 2019 Comments Off on Two doctoral/postdoctoral positions in 1) high-throughput materials discovery, 2) HPC/HTC/HPDA software engineering

Two doctoral/postdoctoral positions are available in the Laboratory for Theory and Simulation of Materials ( at EPFL in Lausanne, Switzerland, under the supervision of Dr. Giovanni Pizzi and Prof. Nicola Marzari.
Outstanding candidates are sought with a strong background in the physical sciences and engineering alongside a passion for programming. Candidates are expected to show excellent work ethics and to feel at home working in teams.

These job openings provide the opportunity to join an exciting and very driven international team at the forefront of research in the field of materials discovery and design, enabled by AiiDA (, an open-source python framework for automated workflow management and provenance tracking. The candidate will join the scientific group at EPFL, collaborating with groups around the world (at universities, research institutes and companies) where AiiDA and its plugins are developed and used to enable the discovery of next-generation materials.

Position 1High-throughput materials discovery: The successful candidate will be involved in materials discovery projects that involve the development of new capabilities dedicated to the automated calculation of advanced materials properties. Typical tasks will involve computing novel properties – from thermodynamics to spectroscopies; enabling novel methods; increasing the automation and robustness of the calculations; automatic optimisation of parallelisation parameters to maximise performance of the simulation codes on next-generation exascale architectures.

Position 2Convergence of HPC/HTC/HPDA on exascale machines: The successful candidate will be involved in implementing new features in AiiDA, focusing on its scalability towards exascale systems, and in particular on calculation throughput and on unlocking seamless management and analysis of large amounts of interconnected data. Possible tasks will include object-store integration, advanced data sharing capabilities, or improved deduplication of data in the file repository and in the database. This position will involve also code maintenance and releases (for AiiDA core or the AiiDA-Quantum ESPRESSO plugins), AiiDA user support, and deployment using various technologies (PYPI, conda, docker, virtual machines via ansible, …).

The positions are funded by the European Centre of Excellence MaX “Materials design at the Exascale” (, where the EPFL MaX team leads the work package “Convergence of high-performance computing, high-throughput computing and high-performance data analytics”, and by the Open Science Platform of the Swiss MARVEL NCCR (, dedicated to the promotion of Open Science and of the technologies that enable it. Both projects support the development and extensive application of AiiDA and of its plugins (over 30 different materials science codes are already interfaced with AiiDA, see full list on the AiiDA plugin registry:

For best consideration, applications should be submitted by Nov 24th, 2019; the positions will remain open until suitable candidates have been found.

Additional information on the selection criteria and requirements, the work environment and how to apply can be found at