The success and widespread use of the next generation of quantum technology will fundamentally depend on the materials used to make them. One of the leading classes of materials for these applications is colour centres in crystalline semiconductors (such as the well-known nitrogen-vacancy centre in diamond), thanks to their stability, long spin coherence lifetimes, and ability to operate near room temperature. Despite significant advances in the last few years, there are still fabrication challenges associated with the leading candidate systems of this class, as well as issues to overcome around environmental interactions. There is therefore still intense research interest in identifying new candidate colour centres for quantum technology applications, with the aim of improving on the state-of-the-art.

First principles modelling is a vital tool in this endeavour, as it allows us to explore the vast range of possible colour centres efficiently. This includes establishing which defect complexes are energetically favourable, how mobile they are, their excited state properties, and the influence environmental effects can have on these properties. With this information in hand, we can computationally screen candidate systems, using theory to guide experiment and industry towards new materials.

In this PhD project, we will make use of cutting-edge computational methods, including linear-scaling time-dependent density functional theory (LS-TDDFT), quantum embedding, and machine learning potentials, to systematically explore this vast space for novel candidate defects for quantum technology applications. The initial focus will be on complexes formed around implanted ions from across the periodic table, particularly focusing on Group IV, Group V, and the transition metals. This will initially be focused on diamond as a host material, but will expand out to explore candidates in host materials such as silicon, SiC, GaN, and others. The simulations performed within the project will provide insight into the fundamental physics of these systems, their robustness against external perturbations, and their suitability for how best to fabricate them. An important aspect of this work will be comparing results and predictions against experimental data where available; there will also be the opportunity to collaborate with world-leading experimental groups in this area.

If the student is interested, there will also be scope within the project for developing more powerful computational modelling methods for describing complex systems at a quantum mechanical level, based on quantum embedding. This development work would be done alongside other members of the group.

This project will suit a student with an interest in computational modelling and/or materials for quantum technology, and a background in physics, chemistry, materials science, or related disciplines. An interest in code development, especially for materials modelling software, would be beneficial, but not necessary.

Eligibility

Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.

Funding

At Manchester we offer a range of scholarships, studentships and awards at university, faculty and department level, to support both UK and overseas postgraduate researchers applying for competition and self-funded projects.

For more information, visit our funding page or search our funding database for specific scholarships, studentships and awards you may be eligible for.

Please discuss funding opportunities with the supervisor.

Before you apply

We strongly recommend that you contact the supervisor(s) for this project before you apply. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.

How to apply

Apply online through our website: https://uom.link/pgr-apply-2425

When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.

After you have applied you will be asked to upload the following supporting documents:

• Final Transcript and certificates of all awarded university level qualifications
• Interim Transcript of any university level qualifications in progress
• CV
• Supporting statement: A one or two page statement outlining your motivation to pursue postgraduate research and why you want to undertake postgraduate research at Manchester, any relevant research or work experience, the key findings of your previous research experience, and techniques and skills you’ve developed. (This is mandatory for all applicants and the application will be put on hold without it).
• Contact details for two referees (please make sure that the contact email you provide is an official university/work email address as we may need to verify the reference)
• English Language certificate (if applicable)

If you have any questions about making an application, please contact our admissions team by emailing [email protected] .

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.

We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.

We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).