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Postdoc: high-throughput computational materials ... (1 reply)

rzk
2 years ago
rzk 2 years ago

The Khaliullin group (McGill) is accepting postdoctoral applications in the area of high-throughput computational design of 2D materials for electronic and clean energy applications. The emphasis of the project is on the development of electronic structure and machine learning methods for rapid materials screening.

Required qualifications:
* Ph.D. within the last 4 years in physics, chemistry, computer science, applied mathematics, materials science, or any relevant discipline;
* Established publication record in method development;
* Solid programming skills;

Desired qualifications:
* Knowledge of numerical methods and algorithms, particularly linear algebra, statistics, optimization;
* Working knowledge of electronic structure methods (e.g. DFT) for periodic systems.
* Familiarity with machine learning methods and especially their applications in materials modeling;

Shortlisted candidates will be asked to complete a short skills test and then will be contacted individually for an online interview.

Offer: The initial appointment is for one year and will be extended annually based on performance.

Please send your application with a CV to Prof. Rustam Khaliullin at [email protected]

Malik
2 years ago
Malik 2 years ago

This is Malik Waqar Arshad, an expected PhD graduate student (31/08/2022) of the University of Science and Technology (UST), Korea Research Institute of Chemical Technology (KRICT), South Korea. I am writing to express my sincere interest in the Postdoctoral Research Fellow position in the area of Computational Catalysis. I strongly believe the nature of my research relates to your lab’s research goals because of my electronic structure (DFT) calculation and Machine Learning (minor) research expertise.




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Ab initio (from electronic structure) calculation of complex processes in materials