Scholarship

Digitally Enabled Self-Optimisation of Heterogenous Chemical Processes

University of Leeds Original Source

About This Opportunity

This PhD research project focuses on developing an advanced platform utilizing AI and self-optimizing reaction technology to improve the efficiency and effectiveness of heterogeneous chemical reactions, thereby accelerating product development. The project aims to expand automated reaction platforms beyond homogeneous reactions to heterogeneous reactions, which constitute 75-80% of reactions in pharmaceutical synthesis. The research will combine automated reaction platforms with optimization algorithms to create Self-Optimization Flow Reactors (SOFRs) for heterogeneous processes. This industrially supported project builds on collaboration between the University of Leeds and Dr Reddy's Ltd, harnessing complementary expertise to address real-world challenges in pharmaceutical synthesis and chemical manufacturing.

42 - 43 mo

1 awards

research chemical engineering process engineering artificial intelligence machine learning automation heterogeneous reactions pharmaceutical synthesis self-optimization flow chemistry organic synthesis

Who Can Apply

Region: United Kingdom
Citizenship: United Kingdom
Residency: United Kingdom
Project in: United Kingdom
Applicants: individual
Organizations: academic

Application Details

Stages

1 single_stage

Required documents

cv transcripts cover_letter

Review process

Competitive selection based on academic merit through EPSRC Faculty Doctoral Landscape Award Competition

Additional benefits

training

Restrictions

geographic_restrictions

External Application

This opportunity requires you to apply directly on the funder's website.

Apply on External Site

Key Information

Award Amount: £20780.00 - £20780.00
Application Deadline: February 27, 2026 at 23:59 UTC

Due in 40 days

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