We have recently developed a novel metaheuristic methodology for optimizing the distribution of atoms and vacancies in solid-state materials. Our approach is currently programmed in the package Julia and has been tested in the solid-state electrolyte LLZO.

The researcher will rewrite/reformat the code, as well as write a manual to share it with the wider community. He/she will also investigate the optimal set of parameters to maximize the algorithm’s performance, and work on the implementation of additional features.

Deadline: 30 September 2022

Applications at: http://www.bcamath.org/en/research/job/ic2022-08-research-technician-on-metaheuristic-optimization-of-solid-state-materials

Requirements:
• M.Sc. or B.Sc. degree in Mathematics, Statistics, Computer Science and related disciplines.
Skills and track record:
• Good interpersonal skills.
• Demonstrated ability to work independently and as part of a collaborative research team.
• Ability to effectively communicate and present research ideas to researchers and stakeholders with different backgrounds.
• Fluency in spoken and written English.

The preferred candidate will have:
• Solid programming skills in Julia. Candidates without specific knowledge of Julia but excellent skills in structurally similar languages such as Python, MATLAB, C++ or Ruby may be considered.
• Background in optimization methods. Specific knowledge in metaheuristic techniques such as simulated annealing of harmonic search is highly desirable.
• Experience with molecular dynamics codes (GROMACS, LAMMPS, etc.) is desirable.