PhD studentship in Computational Prediction of Novel Thermoelectric Semiconductors


Closing date: 31 July 2021 or as soon as an appropriate candidate is found

This position is fully funded by the UCL-A*STAR Collaborative Programme via the Centre for Doctoral Training in Molecular Modelling and Materials Science (M3S CDT) at UCL. The student will be registered for a PhD at UCL where he/she will spend year 1 and the first six months of year 4. The second and third years of the PhD will be spent in IMRE of A*STAR in Singapore. The studentship will cover tuition fees at the Home rate, and an annual stipend of no less than £17,285 increasingly annually with inflation (tax free) pro rata in years 1 and 4. During years 2 and 3, the student will receive a full stipend directly from A*STAR. In addition, A*STAR will provide the student with one-off relocation allowance. 

Due to funding restrictions, this studentship is only open to UK nationals or EU nationals with settled/pre-settled status. Please note that we are currently seeking clarity from the Department for Education on how EU students with pre-settled and settled status will be considered in terms of fee status as the studentship only covers home fees.

Start Date: 27 September 2021

Location: London (1.5 years), Singapore (2 years)

Objective To use state-of-the-art computational chemistry techniques to predict the performance of novel semiconductors for thermoelectric energy generation

The Project As the global demand for energy grows inexorably, renewable energy production is becoming increasingly important. Thermoelectrics (TEs) allows us to convert heat (temperature differences) directly into energy using a phenomenon called the Seebeck Effect. Heat to electricity conversion in thermoelectric systems will play an important role in future energy generation and efficiency. Existing and potential applications of thermoelectric systems include: industrial waste heat recovery; transport heat recovery; radioisotope power systems; space exploration; cooling optoelectronic components; mass-market refrigeration; heat sensors. 

In this project we will use computational techniques to understand the defect chemistry and thermal transport properties of a range of potential thermoelectric materials in the Materials Theory Group ( at UCL, and at IHPC ( at A*STAR, and our computational predictions will feed into the Accelerated Materials Development for Manufacturing Programme at IMRE A*STAR led by Professor Hippalgaonkar. (

The Candidate

The successful applicant should have or expect to achieve at least a 2.1 honours or equivalent for undergraduate degree in Chemistry, Physics, Materials Science or a closely related discipline. The successful applicant will demonstrate strong interest and self-motivation in the subject and the ability to think analytically and creatively. Good computer skills, plus good presentation and writing skills in English, are required. Previous research experience in Computational Chemistry/Physics and/or coding is highly desirable but not necessary as training will be provided.

Please contact Professor David Scanlon ( for further details or to express an interest.


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