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Project Code

2025_053

Start date

1 October 2026

Primary supervisor

Dr Filippo Prischi

Secondary supervisor

Dr Olivier Pardo

Topic Areas

AI, Machine Learning, and Multimodal Data

Co-Funded

De novo molecular generation and property optimization using multi-objective Monte Carlo Tree Search

1. Background: This PhD project aims to develop and experimentally validate a novel AI tool for de novo drug designing. Developing new medicines requires considering extremely large numbers of molecules to identify suitable candidates for further investigation as therapeutics. However, traditional medicial chemistry approaches allow to explore only a small portion of the 1e+63 drug-like molecules predicted to be synthetically accessible. This project will integrate advanced machine learning techniques with molecular modelling and experimental biophysics to de novo designing compounds that bind with high affinity to selected pockets on any macromolecule of interest.

2.Novelty & Importance: This PhD project represents a novel integration of statistical search methods, explainable AI, and structural biology for molecular design. It advances the frontier of AI-driven drug discovery and promises a cost-effective, rapid, and chemically original alternative to conventional drug discovery pipelines. By lowering technical and financial barriers, the platform will enable academic and industrial researchers to tackle urgent therapeutic challenges, including neglected or hard-to-drug targets. Ultimately, this project will have a significant international impact by demonstrating the feasibility of targeting biomarkers and therapeutic avenues that have previously resisted classical approaches.

3.Aims & Objectives: This PhD project aims to develop and experimentally validate a novel AI tool: DrugSynthMC.v2 – an upgraded version of DrugSynthMC fine-tuned for the de novo generation of customized drugs with high affinity for macromolecules of interest.

The specific objectives are to:

1. Develop DrugSynthMC.v2.
2. Validate DrugSynthMC.v2 in silico.
3. Incorporate statistical and chemical compound optimization strategies.
4. Test DrugSynthMC.v2 on a non-conventional drug target.
5. Experimentally validate DrugSynthMC.v2.

We are now accepting applications for 1 October 2026

How to apply

Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.

Important information for International Students:

It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.

How to apply

Closing date: 12 January 2026 (23:59 hrs GMT)

Create an account with King’s Apply.

Apply to the EPSRC DRIVE-Health: Centre for Doctoral Training in Data-Driven Health MPhil/PhD (Full-time).

Please ensure you read the full information required on our Apply page, particularly relating to Personal Statement and Supporting Information.

Complete the following sections of the application with all the relevant information.

A PDF copy of your CV should be uploaded to the Employment History section.
A 500-word personal statement is required outlining your motivation for undertaking postgraduate research with the CDT, and you only need to choose one way to provide it. You can either type it directly into the application form (maximum 4,000 characters) or upload it as a separate document if you have a longer statement (maximum two pages).
Please nominate up to 3 projects of particular interest by quoting the project codes in the research proposal section of the online application form.

Funding:

Please choose Option 5 “I am applying for a funding award or scholarship administered by King’s College London” in the funding section.
Under “Award Scheme Code or Name” enter “EPSRC DRIVE-Health 2026”.

Failing to include one of these codes might result in you not being considered for funding.

Questions marked * are mandatory and you will not be able to submit without answering.

Non-EU international applicants are advised that ATAS may be required. While there is no charge to apply for ATAS, processing can take up to 3 months. Please read the Important Information for International Students.

Apply Now

Funding

Enhanced Studentships to Attract Top Talent

Each studentship is fully funded for 4 years.

This includes tuition fees, a stipend and a generous allowance for project consumables.

Tuition Fees: these will be covered for both Home and International students.

Stipend: students will receive a tax-free living allowance of £25,403.40 per year (current projection for Academic Year 2026/27).

Research Training Support Grant (RTSG): up to £20,000 over 4 years for research consumables and attending national and international conferences.

International

Important Information for International Students

It is the responsibility of the student to apply for their Student Visa.

Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study.

Additionally, depending on your chosen project, some nationals may need to apply for an Academic Technology Approval Scheme (ATAS) certificate prior to applying for a visa. The ATAS application process can take up to 3 months and so it is essential that you apply for this early. Please note the following:
• If you need to apply for a student visa, you cannot submit your visa application until your ATAS certificate has been issued.
• If you are applying for any other visa, you cannot enrol at King’s and start your programme unless your ATAS certificate has been issued.
• If you apply late, you may not be able to join on the expected entry point and your registration may be postponed

Please review the following article for further information on the ATAS certificate and how to apply:Do I need ATAS clearance before I start my course at King’s?

For further advice, please contact the Visas & International Student Advice as soon as possible.

Eligibilty

Academic Requirements and Eligibility

We welcome eligible Home and International applicants from any personal background who are pleased to join diverse and friendly research groups.

Open to Home and International applicants.

Applicable level of study: Postgraduate research.

English Language Requirements (Band D)
Based on the IELTS test scoring system, this programme requires that successful candidates achieve the following level of English before enrolling. Successful applicants’ offer letters will include information about when they must have achieved this standard.
Overall: 6.5
Listening: 6
Speaking: 6
Reading: 6
Writing: 6

Visit our admissions webpages to view our English language entry requirements.

Next steps

For project-specific queries, please contact the main supervisor before you submit your application.

Applications submitted by 12 January 2026 (23:59 GMT) will be considered by the EPSRC DRIVE-Health Centre for Doctoral Training. We will contact shortlisted applicants with information about the next stage of the recruitment process.

Candidates will be invited to attend an interview. Interviews are scheduled to take place in March/April 2026.

Project selection will be through a panel interview chaired by either Professor Richard Dobson or Professor Vasa Curcin (Centre Co-Directors), followed by an informal discussion with prospective supervisors.

For any other questions about the recruitment process, please email us at drive-health-cdt@kcl.ac.uk.