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PhD position in thermoelectrics (No replies)

jb2191
3 years ago
jb2191 3 years ago

About the Project

The project aims to develop Artificial Intelligent (AI) algorithms, which can map multi-functional material properties with multi-objective search algorithms to accelerate the discovery of novel materials exhibiting desirable functional properties. Some of these desirable characteristics would be piezoelectric or thermoelectric properties, allowing the novel materials to be used in the development of highly robust and miniaturised printable sensors.

Furthermore, such an AI model will be integrated with a suitable time integrator such as molecular dynamics to validate the predicted properties to yield a complete property map which can be validated by experimental flexible printing using a ink printing method.

Additionally, the project aims at the autonomous discovery of chemical rules from large-scale data via semi-supervised learning and local descriptor search. Infusion of domain knowledge will be tried out to make the ML framework more data efficient.

To utilise data from multiple experimental and computational sources, databases such as Materials Genome Initiative with varying levels of fidelity, will be use with inclusion of first principal DFT/ab-initio calculations.

Works with similar approaches are growing in the literature and some of these works will readily guide the methodology required in this project. In this regard, the following references will serve as suitable reference papers:

 

https://doi.org/10.1002/adma.202003206

DOI: 10.1039/d0ta00690d

DOI: 10.1126/sciadv.aaq1566

Requirements: Applicants must be of outstanding academic merit and should have (or be expected to gain) either a first class or an upper second-class Honours degree (or the international equivalent), or an MSc/MRes with distinction. Enthusiastic and self-motivated candidates from all countries with a background in either Engineering, Materials Science, Physics or Mathematics or a related discipline are encouraged to apply. Candidates should be able to demonstrate that they are highly motivated, have excellent communication skills and undertake challenging tasks using their own initiative.

 

Funding Notes

We are offering a number of funded PhD scholarships. These studentships are available to UK nationals & EU citizens and overseas applicants. Those in possession of their own funding (e.g. via a non-EU government scholarship) are also welcome to apply for a place of study.

 

Please get in touch with Prof Saurav Goel (PI) and Dr Jonathan Bean (co-PI) with your CV if you are interested in applying

[email protected]

[email protected]

 




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