Smart Crystals: Computer Vision and Machine Learning Assisted Industrial Crystallization Modeling and Control

This AstraZeneca-funded project (Macclesfield, U.K.) addresses key challenges in automating crystallization processes, a crucial separation and purification technique widely used in producing fine chemicals, including pharmaceuticals. By leveraging state-of-the-art advances in computer vision and machine learning, we aim to manipulate Particle Size and Shape Distribution (PSSD) under industrially relevant conditions.

Crystallization processes typically yield powders with varying particle properties. Research has shown that equant-shaped crystals with narrow size distributions and minimal fine particles are ideal, as nonequant shapes (e.g., needles, platelets) complicate downstream processes like filtration, drying, and formulation. Recent breakthroughs in process monitoring and computational techniques, including foundational work by Dr. Rajagopalan’s group, have shifted the focus toward directly manipulating PSSD, especially for challenging elongated and plate-like particles, commonly encountered in the pharmaceutical and agrochemical sector.

A cornerstone of this project is DISCO, a stereoscopic imaging device enabling real-time PSSD monitoring during crystallization. This tool, combined with advanced population balance modeling aided by scientific machine learning, will enable real-time feedback control, achieving precise particle size and shape outcomes. These innovations will empower the broader crystallization community to overcome longstanding challenges in process automation, advancing the field toward Pharma 4.0 standards.

Eligibility

Applicants should have or expect to achieve a first-class honours degree in Chemical Engineering. 

Funding

This 3.5 year PhD project is funded by AstraZeneca and includes a 3-month placement in AstraZeneca’s facility in Macclesfield. The tuition fees will be paid and a tax free stipend based at the standard UKRI rate will be paid (£19,237 for 2024/25). The start date is October 2025. This is project is for home students only, i.e. UK nationals or Europeans with pre-settled status.

Before you apply

Applicants are strongly encouraged to contact Dr. Ashwin Kumar Rajagopalan with a cover letter and a copy of their CV at a.rajagopalan@manchester.ac.uk for informal enquiries. Applicants can also visit ash23win.github.io for further information regarding Dr. Rajagopalan’s research group.

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 FSE.doctoralacademy.admissions@manchester.ac.uk.

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).

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