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We are looking for highly motivated individuals who are passionate about contributing to new discoveries in drug discovery bioscience through the application of the latest techniques in AI and data science.

We welcome applications from candidates who hold a masters degree at distinction or first class level, or have gained equivalent experience, in Computer Science, Bioinformatics / Computational Biology, Biochemistry, Biotechnology, Biology, Pharmacology, Medicinal Chemistry, Chemistry or other relevant fields. We accept applicants with a first class Bachelors degree who do not hold a Masters degree, provided the applicants provide evidence of equivalent research experience, industry experience, or specialist training. Programming skills are strongly desirable and you will be confident in performing data wrangling and analysis in a language such as Python, R or C++, or can demonstrate the ability to acquire the necessary level of programming skills.

We particularly encourage students from groups that are currently underrepresented in postgraduate science research, including black and minority ethnic students and those from a socio-economically disadvantaged background.

Part-time study is an option for some projects. Please specify this as part of your application if relevant.

Eligibility 

We appreciate all talent and skills, and we welcome applicants of all backgrounds and identities. In line with the UKRI guidelines, our applications are open to both home and international students who meet the programme entry criteria, with up to 30% of our places being available for international students. Further details on UKRI student eligibility criteria is detailed in the UKRI Postgraduate funding guide. 

To be classed as a home student, candidates must meet the following criteria set out in the UKRI Training Grant Terms & Conditions:

• Be a UK National (meeting residency requirements), or
• Have settled status, or
• Have pre-settled status (meeting residency requirements), or
• Have indefinite leave to remain or enter

If a candidate does not meet the criteria above, they would be classed as an International student.

If you obtained your qualifications outside of the UK, check country/region specific information on the Queen Mary Webpage.

Applicants whose first language is not English will be required to provide evidence of their English language ability, in line with QMUL admissions policy for postgraduate research programmes. The minimum requirements for the AIDD Doctoral training programme are:

• IELTS Academic: Minimum score of 6.5 overall including 6.0 in Writing, Reading, Listening and Speaking. 

For information on all accepted English language tests that are deemed equivalent to these scores, please see the Queen Mary webpage on Language Requirements. 

Applications are currently being accepted for candidates to join the AI for Drug Discovery Programme. Applicants must ensure that you submit your application, and all required attachments prior to the deadline outlined for the project you are applying for.  

You can find projects available for the 2025-2026 cohort noted on the projects pages. Please ensure that you have identified a project prior to submitting an application. You can apply for a maximum of 2 projects. 

The Programme has two deadlines, and we encourage you to apply as soon as your application is ready.

• Round 1: February 2^nd 2025: Applications must be received by 11.59pm (GMT) on February 2^nd 2025 in order to be considered for Round 1.
• Round 2: May 5^th 2025: Applications must be received by 11.59 (GMT) on May 5^th 2025 in order to be considered for Round 2.

 Applications will be accepted for Round 2 from March 2025 onwards, and projects may be allocated in Round 1 and therefore not available in Round 2.

Once you have identified a project(s) to apply for, you will need to complete an online application form via the Queen Mary Admissions Portal. The programme code you will need to select is RFQM-I9EE-09 (PhD FT Artificial Intelligence for Drug Discovery).

As part of the application, you will need to attach the following documents. Note, applications that do not include all the following documents will be considered as incomplete.

• A completed copy of the AIDD Anonymised Application Form 2025-2026 [DOC 88KB]*
• Copy of your CV
• Copy of your degree certificate(s) and transcripts
• Certificate of English Language, if required (IELTS, TOEFL or equivalent as per above)
• Details of two Referees

*Applications are shortlisted based on the information provided in the anonymised application form. This should be uploaded to your application in the Queen Mary Admissions Portal under the personal statement section. The form will be separated from the rest of your application at the shortlisting stage, and the Selection Panel will only see the information in the anonymised form. 

Candidates do not need to upload a specific research, or personal statement, as this information will be captured in the AIDD Anonymised Application Form.

We have prepared a Guide on how to complete the application form. We recommend you review this in advance of submitting your application.

Submitted applications will be reviewed by a panel of academics from the AI for Drug Discovery programme, and shortlisted candidates will be invited to attend an interview with the project team of their chosen project. If you have identified 2 projects in your application, you may be invited to attend an interview for both projects.

The selection panel will initially review the material submitted in the AI for Drug Discovery Application form that candidates will complete, and upload as part of their application via the Queen Mary Admissions Portal. This form is designed to be anonymised to support a fair assessment.

Successful candidates will be able to demonstrate:

• Academic Track Record: A strong academic record, with good grades or distinction. 
• Motivation for PhD Studies: Strong motivation to pursue a PhD degree, for example through evidence of seeking research experience, and understanding of how their skills and experience to-date will support them. 
• Fit to Chosen Project(s): Good fit to chosen project and supervisor, demonstrating a clear understanding of the chosen project and how their experience, interests, and skills align to it.

Applicant's achievements will be considered within the context of their individual circumstances.

We have put together this list of frequently asked questions based on enquiries received for other doctoral training programmes. If your question isn’t answered here please contact us on  deri@qmul.ac.uk and one of our management team will get back to you as soon as possible. We will update this list of FAQs with commonly asked queries that we receive.

Is this programme for me?
Given the cross-disciplinary nature of the programme, we expect to recruit students from a range of academic backgrounds, from computer science to biochemistry. The specific balance between areas in which each student will be trained will therefore differ significantly as the students develop into interdisciplinary researchers. While this programme is primarily focussed on computer-based research, QMUL will provide with a useful route to experimental validation of novel findings, allowing close integration of experimental biology and data-driven and modelling approaches.

What fees do I have to pay?
International and home postgraduate student fees are covered by most studentships in full. We have limited number of places for international PhD students, in line with requirements from our funder, and each project will outline what the award will cover. 

Can the studentship be undertaken part time?
Requests for undertaking PhD research part-time can be considered. Note that this will extend the overall duration of your PhD training. If you want to pursue your PhD training on a part-time basis, please make sure to indicate this in your application, explaining why you think this is the best option for you.

Is this programme available remotely?
This is not a distance learning programme, students are expected to be living in the UK throughout the programme in order to attend some courses, training and industry placements in person.

What documents do I need to submit with my application?
Applications should be submitted via the Queen Mary Admissions Portal and you will need to include the below documents:

• A copy of the completed AIDD Anonymised Application Form 2025-2026 [DOC 88KB]
• Copy of your CV
• Copy of your degree certificate(s) and transcripts
• Certificate of English Language, if required (IELTS, TOEFL or equivalent as per above)
• Details of two Referees

The AIDD Anonymised Application Form will be used to support anonymised shortlisting, and will be separated from your application at the shortlisting stage.

How does the industry placement work?
Industry placements will be agreed with your supervisory team, and may take place in one block, for example a period of 3months, or be spread over the course of the programme depending on the needs of your project. You will be party to an agreement between Queen Mary, the Industry partner, and yourself which outlines the additional contribution that the Industry partner will make towards your studentship, to facilitate engagement and visits to their offices. This typically is a stipend top-up to cover additional travel, and accommodation during the period of a placement, however this does vary and will be agreed based on the requirements of your specific project, and you may therefore find that it varies between students on the programme.

How does the interview work?
If your application is shortlisted, you will be invited to attend an invite with the primary and secondary supervisors on your chosen project. Interviews will either take place in person, or via Zoom, and will typically last up to 30 minutes. You can expect the interview panel to ask you about your motivation to pursue a PhD, your experience to-date, and its fit to the chosen project, as well as why you might wish to undertake the project you have chosen.

How should I select my References?
It is important that the individuals you submit as referees can comment on your academic and professional experience, as these will be used in the shortlisting of your application. We recommend that you approach your chosen referees in advance and notify them that you are applying and wish to list them as a reference. Ensure that you discuss the project(s) that you are considering applying for, and that you give them sufficient notice so that they have time to provide a reference by the deadline.

At least one your references should be from an academic setting, ideally someone who can comment on your research abilities. This could be a supervisor on a project, or when conducting lab-work for example. A personal tutor may be a good choice if they are able to comment on your interests and abilities, as well as your personal goals, or a previous employer if they are able to comment on your interests or skills related to your research area.

Do I need to contact the Supervisor of my chosen project before applying?
You do not need to contact the supervisor(s) listed on the project you are interested in prior to applying. If you have a question on the project, or are unsure on anything, you can reach out to the supervisor directly or you can contact deri@qmul.ac.uk who will be able to provide further support.

When will I hear the outcome of my application?
Once the deadline for your chosen Round has passed, your application will be reviewed by a panel of academics from the AI for Drug Discovery programme, and shortlisted candidates will be invited to attend an interview with the project team of their chosen project. Invites to interview should be issued to candidates within 6 weeks of the Round closing. We intend to notify unsuccessful candidates for Round One in mid-March, and Round Two in mid-June. Due to the volume of applications, we will not be able to offer feedback to candidates who are not invited to interview.