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M3S Vacancies

General Information

The M3S CDT will have a number of PhD studentships available for September 2022 start. If you are interested in any project(s) listed, you should initially contacted the supervisor(s) with a degree transcript and a motivation letter expressing interest in the project. Informal inquiries are encouraged.
Any admissions queries should be directed to Dr Zhimei Du
z.du@ucl.ac.uk

A 3-Year PhD Studentship in High-throughput screening of metal catalysts supported by zeolites for CO2 transformation (D/L:15/04/2022)

Supervisors: Prof. Ben Slater (UCL), Dr.  Jia Zhang (IHPC, A*STAR, Singapore)
Application deadline: 15/04/2022 
Interview date:  TBC (2 to 4 weeks after the application close date)

Start date: 26 September 2022
Location: London (1.5 years), Singapore (2 years)
Subject areas: Catalysts, Chemical modification, High Performance Computing, Machine Learning

The studentship
This position is fully funded by the UCL-A*STAR (Agency for Science, Technology and Research, Singapore) 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 the Institute of High Performance Computing (IHPC) of A*STAR in Singapore. The studentship will cover tuition fees at the home rate, and an annual stipend of no less than £17,609 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 a one-off relocation allowance.


The project
Prof Ben Slater of UCL (Chemistry), UK and Dr  Jia Zhang of IHPC (A*STAR), Singapore are launching an interdisciplinary, combined theory and experimental study into identifying the best performing metal nanoparticle catalyst within selected zeolites for transforming CO2 into useful chemical feedstocks such as methanol, formic acid and ethanol. The project will benefit from experimental support from Prof Ning Yan at NUS, a world renowned expert on developing catalysts for upscaling small molecules. The appointed student will spend the initial phase of the project performing fundamental computer simulations to examine, at the molecular level, the transformation mechanism of CO2 to methanol on metal nanoparticles. Next, the student will assess (via screening) how doping with metals such as Pd affects the energetics and barriers in the transformation. This step will seek to identify descriptors so that machine learning protocols can be developed and applied to accelerate the identification of the most promising functional metal nanoparticle. The final step will investigate where the nanoparticles sit within the zeolites of interest (e.g. zeolite Y, zeolite A and ZSM-5) and how the reaction profiles for CO2 upscaling are affected. The most promising predicted materials will be investigated by Prof Yan’s group and the experimental results cross-referenced with the predictions to establish a feedback loop to refine the machine learning and high-throughput aspects of the research.

The candidate
The applicants should have, or be expecting to achieve, a first or upper second-class integrated masters degree (MSci, MChem, etc.) or 2:1 minimum BSc plus stand-alone Masters degree with at least a Merit in Chemistry or materials science. The successful applicant will demonstrate strong interest and self-motivation in the subject, good experimental practice 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 contributing to a collaborative interdisciplinary research environment is highly desirable but not necessary as training will be provided.

Interested candidates should initially contact the supervisors (Prof Ben Slater b.slater@ucl.ac.uk and Dr Jia Zhang zhangj@ihpc.a-star.edu.sg)  with a degree transcript and a motivation letter expressing interest in the project. Informal inquiries are encouraged.

Please note that a suitable applicant will first be required to complete MS Form entitled Application for Research: degree Chemistry programme. The next step is to complete an electronic application form at http://www.ucl.ac.uk/prospective-students/graduate/apply (please select Research degree: Chemistry programme).

All shortlisted applicants will be invited for the interview no more than 4 weeks after the application deadline.

Any admissions queries should be directed to Dr Zhimei Du z.du@ucl.ac.uk

Applications are welcome from UK nationals, EU nationals with settled/pre-settled status. Please note that the studentship only covers home fees. The updated rules for eligibility for home fees for next year are available at View Website.

Applications will be accepted until 15/04/2022.

A 3-Year PhD Studentship in Metal Ions Containing Porous Materials for Activation of C1 and Bio mass conversions (D/L:15/04/2022)

Supervisors: Prof Ivan Parkin, Prof Gopinathan Sankar (UCL) and Dr Armando Borgna (ICES, A*STAR, Singapore
Application deadline: 15/04/2022 
Interview date: TBC (2 to 4 weeks after the application close date)

Start date: 26 September 2022
Location: London (1.5 years), Singapore (2 years)

The studentship
This position is fully funded by the UCL-A*STAR (Agency for Science, Technology and Research, Singapore)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 the Institute of Catalysis and Engineering Science (ICES) of A*STAR in Singapore. The studentship will cover tuition fees at the home rate, and an annual stipend of no less than £17,609 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 a one-off relocation allowance.

The project
The aim of the project is to investigate selected micro porous silicates and aluminophosphate based catalysts for acid catalysed reaction for dehydration and isomerisation reactions. We will focus on both the well-defined porous zeolitic solids (ZSM-5, SAPO-34 and SAPO-5 for example) to examine the role of acid properties on the catalytic reactions. Copper and zinc containing systems will play a major role in these as they ae shown to promote methane activation process. We will characterise these materials extensively, in particular using X-ray diffraction, X-ray absorption spectroscopy and FTIR techniques. Several independent catalytic tests will be carried out and identify the suitable reaction conditions to carry out in situ characterisation of the working catalysts.

The candidate
The applicants should have, or be expecting to achieve, a first or upper second-class integrated masters degree (MSci, MChem, etc.) or 2:1 minimum BSc plus stand-alone Masters degree with at least a Merit in Chemistry or materials science. The successful applicant will demonstrate strong interest and self-motivation in the subject, good experimental practice 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 contributing to a collaborative interdisciplinary research environment is highly desirable but not necessary as training will be provided.

Interested candidates should initially contact the supervisors (Prof. Ivan Parkin i.p.parkin@ucl.ac.uk; Prof. Gopinathan Sankar g.sankar@ucl.ac.uk) with a degree transcript and a motivation letter expressing interest in the project. Informal inquiries are encouraged.

Please note that a suitable applicant will first be required to complete MS Form entitled Application for Research: degree Chemistry programme. The next step is to complete an electronic application form at http://www.ucl.ac.uk/prospective-students/graduate/apply (please select Research degree: Chemistry programme).

All shortlisted applicants will be invited for the interview no more than 4 weeks after the application deadline.

Any admissions queries should be directed to Dr Zhimei Du
z.du@ucl.ac.uk

Applications are welcome from UK nationals, EU nationals with settled/pre-settled status. Please note that the studentship only covers home fees.    The updated rules for eligibility for home fees for next year are available at View Website.

Applications will be accepted until 15/04/2022.

A 3-Year PhD Studentship in Designing nanomaterials for low-cost fast pollutant sensing and remediation (D/L:15/04/2022)

Supervisors: Dr Gemma-Louise Davies (UCL), Prof. Xiaodi Su and Dr Zheng Xinting (IMRE, A*STAR, Singapore)
Application deadline: 15/04/2022 
Interview date:  28/04/2022

Start date: 26 September 2022
Location: London (1.5 years), Singapore (2 years)
Subject areas: Nanomaterials, Pollutant sensing, Pollutant remediation

The Studentship
This position is fully funded by the UCL-A*STAR (Agency for Science, Technology and Research, Singapore) 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 the Institute of Materials Research and Engineering (IMRE) of A*STAR in Singapore. The studentship will cover tuition fees at the home rate, and an annual stipend of no less than £17,609 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 a one-off relocation allowance.

The project
Traditional methods of detecting pollutants (e.g. heavy metals, pesticides, antibiotics, drugs) require the use of expensive and specialised equipment. Although providing high levels of sensitivity and low limits of detection, these techniques can be costly and inconvenient. Simple and sensitive colorimetric analysis could provide an ideal opportunity to solve this challenge. Gold nanoparticles, with their well-established aggregation-triggered colorimetric response, provide an ideal route to this. Herein, this mechanism will be exploited in a different way to the current standard, applying the lessons learned in this area to date to develop a new route to nanomaterials with the dual capabilities of selective and specific detection of pollutants and their easy removal for environmental remediation.

The candidate
The applicants should have, or be expecting to achieve, a first or upper second-class integrated masters degree (MSci, MChem, etc.) or 2:1 minimum BSc plus stand-alone Masters degree with at least a Merit in Chemistry, Chemical engineering or Materials science. The successful applicant will demonstrate strong interest and self-motivation in the subject, good experimental practice 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 contributing to a collaborative interdisciplinary research environment is highly desirable but not necessary as training will be provided.

Interested candidates should initially contact the supervisors (Gemma-Louise Davies: gemma-louise.davies@ucl.ac.uk; Xiaodi Su: xd-su@imre.a-star.edu.sg) with a degree transcript and a motivation letter expressing interest in the project. Informal inquiries are encouraged.

Please note that a suitable applicant will first be required to complete MS Form entitled Application for Research: degree Chemistry programme. The next step is to complete an electronic application form at http://www.ucl.ac.uk/prospective-students/graduate/apply (please select Research degree: Chemistry programme).

All shortlisted applicants will be invited for the interview no more than 4 weeks after the application deadline.

Any admissions queries should be directed to Dr Zhimei Du z.du@ucl.ac.uk

Applications are welcome from UK nationals, EU nationals with settled/pre-settled status. Please note that the studentship only covers home fees.   The updated rules for eligibility for home fees for next year are available at View Website.

Applications will be accepted until 15/04/2022.

A 3-Year PhD Studentship in Programmable self-propelled droplets on super-slippery lubricated surfaces (D/L:15/04/2022)

Supervisors: Dr Giorgio Volpe (UCL), Dr  Dan Daniel (IMRE, A*STAR, Singapore)
Application deadline: 15/04/2022 
Interview date:  03/05/2022

Start date: 26 September 2022
Location: London (1.5 years), Singapore (2 years)
Subject areas: Soft Matter, Active Matter, Droplets, Surfaces and Interfaces

The Studentship
This position is fully funded by the UCL-A*STAR (Agency for Science, Technology and Research, Singapore) 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 the Institute of Materials Research and Engineering (IMRE) of A*STAR in Singapore. The studentship will cover tuition fees at the home rate, and an annual stipend of no less than £17,609 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 a one-off relocation allowance.

The project
The transport of droplets on surfaces has broad applications, including handling small amounts of matter, harvesting energy, manufacturing materials, and sensing chemical and biological analytes. A particularly alluring strategy to control droplet motion is the use of super-slippery lubricated surfaces inspired by the Pitcher plant, which can be created by infusing a solid porous material with a lubricating liquid (https://www.youtube.com/watch?v=0RDU7fuZ3EQ). Whilst different methods have been proposed to manipulate droplets on super-slippery lubricated surfaces, these are typically of limited reach and versatility. The aim of this project is therefore to develop a minimally invasive, universal, and scalable method for the manipulation of droplets of any liquid on such surfaces without altering their composition. Specifically, this project will focus on developing a novel noncontact droplet manipulation technique to control the motion of droplets on super-slippery lubricated surfaces. This novel technique will combine vapour-mediated forces and capillary-driven processes to manipulate droplets in pre-defined tracks on such surfaces with fast droplet motion (up to m/s). This novel approach will enable us to use the transport of droplets for energy, manufacturing and sensing applications on super-slippery lubricated surfaces. See https://activematterlab.org/ (Dr Volpe) and https://dropletlab.science/ (Dr Daniel) for more details on our research.

The candidate
The applicants should have, or be expecting to achieve, a first or upper second-class integrated masters degree (MSci, MChem, etc.) or 2:1 minimum BSc plus stand-alone Masters degree with at least a Merit in Physics, Chemistry, Materials Science, Engineering or a related discipline. The successful applicant will demonstrate strong interest and self-motivation in the subject and the ability to think analytically and creatively. An enquiring and rigorous approach to research as well as excellent team-working, computer skills and observational and communication skills (both presentation and writing skills in English) are also essential. Previous data analysis and programming experience is highly desirable. Previous research experience in contributing to a collaborative interdisciplinary research environment would be highly desirable but not essential, as training will be provided.

Interested candidates should initially contact the supervisors, Dr Volpe (g.volpe@ucl.ac.uk) and Dr Daniel (daniel@imre.a-star.edu.sg), with a degree transcript and a motivation letter expressing interest in the project. Informal inquiries are encouraged.

Please note that a suitable applicant will first be required to complete MS Form entitled Application for Research: degree Chemistry programme. The next step is to complete an electronic application form at http://www.ucl.ac.uk/prospective-students/graduate/apply (please select Research degree: Chemistry programme).

All shortlisted applicants will be invited for the interview no more than 4 weeks after the application deadline. The interview process will include a short data analysis project and the preparation of a small report to summarise its results.

Any admissions queries should be directed to Dr Zhimei Du z.du@ucl.ac.uk

Applications are welcome from UK nationals, EU nationals with settled/pre-settled status. Please note that the studentship only covers home fees. 
The updated rules for eligibility for home fees for next year are available at View Website.

Applications will be accepted until 15/04/2022.

A 3-Year PhD Studentship in Predicting Dopability Using Machine Learning (D/L:15/04/2022)

Supervisors: Prof. David O. Scanlon (UCL), Prof. Kedar Hippalgaonkar  (IMRE, A*STAR, Singapore)
Application deadline: 15/04/2022 
Interview date:  29/04/2022

Start date: 26 September 2022
Location: London (1.5 years), Singapore (2 years)

The Studentship
This position is fully funded by the UCL-A*STAR (Agency for Science, Technology and Research, Singapore) 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 the Institute of Materials Research and Engineering (IMRE) of A*STAR in Singapore. The studentship will cover tuition fees at the home rate, and an annual stipend of no less than £17,609 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 a one-off relocation allowance.

Objective

To combine state of the art computational chemistry techniques in combination with machine learning models to predict the dopability of materials

The project
Defects in crystalline solids introduce local and extended imperfections that define their applicability for most technological applications. For example, the ability to have insulating (non-conducting) behaviour is vital for topological insulators or γ-ray detectors, whereas the ability to dope a material to near metallic levels of conductivity is vital for transparent electrodes in optoelectronic devices. In order to predict the functional properties of crystalline materials, one must therefore understand the effect of defects in such solids.  Especially important is the so-called “dopability” of crystals – namely, the ability to predict which dopant atoms can occupy which positions in a crystalline solid and introduce charge carriers to enable functionality. In the era of data-driven research, the ability to screen for materials and compositions that, when doped, give a desired performance, is still an important, unsolved problem.

In this project we will use computational techniques to understand the defect chemistry or a range of materials in the Materials Theory Group (www.davidscanlon.com) at UCL , and our computational predictions will feed into the Machine Learning models developed in the Accelerated Materials Development for Manufacturing Programme at IMRE A*STAR led by Professor Hippalgaonkar. (https://kedarh.wixsite.com/nanotransport).

The candidate
The applicants should have, or be expecting to achieve, a first or upper second-class integrated masters degree (MSci, MChem, etc.) or 2:1 minimum BSc plus stand-alone Masters degree with at least a Merit in Chemistry or materials science. The successful applicant will demonstrate strong interest and self-motivation in the subject, good experimental practice 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/Materials Science and/or coding and/or Machine learning is highly desirable but not necessary as training will be provided.

Interested candidates should initially contact the supervisors, Professor David Scanlon (d.scanlon@ucl.ac.uk) and Professor Kedar Hippalgaonkar (kedarh@imre.a-star.edu.sg) with a degree transcript and a motivation letter expressing interest in the project. Informal inquiries are encouraged.

Please note that a suitable applicant will first be required to complete MS Form entitled Application for Research: degree Chemistry programme. The next step is to complete an electronic application form at http://www.ucl.ac.uk/prospective-students/graduate/apply (please select Research degree: Chemistry programme).

All shortlisted applicants will be invited for the interview no more than 4 weeks after the application deadline.

Any admissions queries should be directed to Dr Zhimei Du z.du@ucl.ac.uk

Applications are welcome from UK nationals, EU nationals with settled/pre-settled status. Please note that the studentship only covers home fees. 
The updated rules for eligibility for home fees for next year are available at  View Website.

Applications will be accepted until 15/04/2022.

A 3-Year PhD Studentship in Computation-driven design of supramolecular organocatalysts (D/L:15/04/2022)

Supervisors: Dr. Tung Chun Lee (UCL), Prof. Yong-Wei Zhang (IHPC, A*STAR, Singapore)
Application deadline: 15/04/2022
Interview date:  TBC (2 to 4 weeks after the application close date)
Start date: 26 September 2022
Location: London (1.5 years), Singapore (2 years)
Subject areas: supramolecular chemistry, host-guest complexes, chemical reaction mechanism, catalysis, generative machine learning, molecular modelling, density functional theory (DFT), ab initio molecular dynamics (AIMD)

The studentship
This position is fully funded by the UCL-A*STAR (Agency for Science, Technology and Research, Singapore) 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 the Institute of High Performance Computing (IHPC) of A*STAR in Singapore. The studentship will cover tuition fees at the home rate, and an annual stipend of no less than £17,609 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 a one-off relocation allowance.

The project
Understanding the mechanism of how molecules react in chemical catalysis is of interest because it can lead to more efficient chemical processes. For instance, in catalyses that involve encapsulation of reactant molecules within a nanoscale cavity (i.e. a “nanoreactor”, as found in zeolites, metal-organic framework and enzymes), it is known that the reaction rate of a specific pathway can be enhanced if the intermediate species are stabilised by interaction with the cavity wall. Nevertheless, the role of nano-cavities in catalytic mechanism is largely unexplored because it is difficult to isolate and study the highly unstable, short-lived reaction intermediates within the “inner phase”, let alone to correlate a number of intermediates throughout a reaction cascade.

This PhD project aims to design supramolecular organocatalysts using computation-driven approaches, which will synergise with the experimental effort led by the Lee group.[1] Promising organocatalysis systems for both experiments and simulations will be designed via computer-aided discovery approaches, e.g. Monte Carlo Tree Search. Design rules for exotic chemistry in supramolecular and catalytic systems will be obtained through computational investigation into selected host-guest complexes using first principle techniques, e.g. density functional theory (DFT) and ab initio molecular dynamics (AIMD).

Please visit our group websites for more details about our research:
http://tungchunlee.weebly.com/
https://research.a-star.edu.sg/researcher/yong-wei-zhang/
[1] “Chemistry inside molecular containers in the gas phase”, Nat. Chem., 2013, 5, 376–382.

The candidate
The successful applicant should have or expect to achieve a 1st or 2:1 class integrated Masters degree (MEng, MSci, MChem etc.) in Chemistry, Physics, Materials Science, or a related discipline. The successful applicant will demonstrate strong interest and self-motivation in the subject, good computational practice 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 contributing to a collaborative interdisciplinary research environment is highly desirable but not necessary as training will be provided.

Interested candidates should initially contact Dr. Tung Chun Lee (tungchun.lee@ucl.ac.uk) with a CV, a degree transcript and a motivation letter expressing interest in the project. Informal inquiries are strongly encouraged.

All shortlisted applicants will be invited to the interview no more than 4 weeks after the application deadline.

Applications are welcome from UK nationals, EU nationals with settled/pre-settled status. Please note that the studentship only covers home fees. 
The updated rules for eligibility for home fees for next year are available at View Website.

Please note that the successful applicant will first be required to complete MS Form entitled Application for Research: degree Chemistry programme. The next step is to complete an electronic application form at http://www.ucl.ac.uk/prospective-students/graduate/apply (Select Research degree: Chemistry programme). Any admissions queries should be directed to Dr. Zhimei Du z.du@ucl.ac.uk

Applications will be accepted until 15/04/2022.

A 3-Year PhD Studentship in Computational Biophysics (D/L:15/04/2022)

Supervisors: Prof. Edina Rosta (UCL), Dr. Marco Klaehn (IHPC, A*STAR, Singapore)
Application deadline: 15/04/2022 
Interview date:  04/05/2022

Start date: 26 September 2022
Location: London (1.5 years), Singapore (2 years)
Subject areas: Catalysis, Biomolecular simulations, Machine learning

The studentship
This position is fully funded by the UCL-A*STAR (Agency for Science, Technology and Research, Singapore) 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 the Institute of High Performance Computing (IHPC) of A*STAR in Singapore. The studentship will cover tuition fees at the home rate, and an annual stipend of no less than £17,609 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 a one-off relocation allowance.

The project
RAS is the most frequently mutated protein in all human cancers, loses its natural catalytic activity, unable to hydrolyse GTP efficiently due to oncogenic mutations. To date, RAS is considered “undruggable” despite its association to multiple of cancers, including adeno-carcinomas and melanoma. We aim to study the catalytic reaction mechanism and to design small molecule ligands that interact with oncogenic RAS mutants and help to shut down aberrant signalling that leads to cancer. We will use computational methods, including state-of-the-art machine learning approaches to achieve our goal, which could revolutionise current cancer therapies, as oncogenic RAS mutations are present in about 30% of all tumours screened, and are frequently associated with cancer types that are resistant to current therapies.

The candidate
The applicants should have, or be expecting to achieve, a first or upper second-class integrated masters degree (MSci, MChem, etc.) or 2:1 minimum BSc plus stand-alone Masters degree with at least a Merit in Physics, Chemistry or related subjects. The successful applicant will demonstrate strong interest and self-motivation in the subject as well as ability to think analytically and creatively. Experience with Linux or/and Python is highly desirable, but not necessary as training will be provided. Good presentation and writing skills in English are required. Previous research experience in contributing to a collaborative interdisciplinary research environment is desirable.

Interested candidates should initially contact the supervisors (Edina Rosta, e.rosta@ucl.ac.uk) with a degree transcript and a motivation letter expressing interest in the project. Informal inquiries are encouraged.

All shortlisted applicants will be invited for the interview no more than 4 weeks after the application deadline.

Any admissions queries should be directed to Dr Zhimei Du 
z.du@ucl.ac.uk

Applications are welcome from UK nationals, EU nationals with settled/pre-settled status. Please note that the studentship only covers home fee.
The updated rules for eligibility for home fees for next year are available at 
View Website.

Applications will be accepted until 15/04/2022.