PhD Studentship - Process Industries: Net Zero - Predictive Modelling of Powder Blending in Con[...] in Newcastle upon Tyne

PhD Studentship - Process Industries: Net Zero - Predictive Modelling of Powder Blending in Con[...] in Newcastle upon Tyne

Newcastle upon Tyne Full-Time 21805 - 21805 £ / year (est.) No working from home possible
Emerging Scholars Council

At a Glance

  • Tasks: Develop predictive models for pharmaceutical manufacturing using advanced simulation and AI-ready modelling.
  • Company: Collaborate with AstraZeneca and Newcastle University on cutting-edge research.
  • Benefits: Receive a competitive stipend of £21,805 plus a £20,000 research training grant.
  • Other info: Join a dynamic team focused on innovative solutions for net-zero processes.
  • Why this job: Make a real impact in the pharmaceutical industry while gaining valuable skills.
  • Qualifications: Must have a minimum 2:1 Honours degree in a relevant field.

The predicted salary is between 21805 - 21805 £ per year.

Newcastle University

Qualification Type: PhD

Location: Newcastle upon Tyne

Funding for: UK Students

Funding amount: £21,805 per annum (2026/27 UKRI rate), and a research training support grant of £20,000.

Hours: Full Time

Placed On: 6th July 2026

Closes: 22nd July 2026

Reference: PINZ11-26

Award Summary

  • 100% fees (UK home only)
  • A minimum tax-free annual living allowance of £21,805 (2026/27 UKRI rate)
  • A research training support grant of £20,000.

Overview

Interested in using advanced simulation, AI-ready modelling and industrial data to accelerate pharmaceutical manufacturing and the delivery of life-saving medicines? This industrially focused project, co-supervised by AstraZeneca and Newcastle University, will develop predictive models for pharmaceutical manufacturing and provide access to industrial data and high-performance computing facilities. You will gain expertise in particle simulation, experimental design, high-performance computing, pharmaceutical manufacturing and predictive modelling; preparing you for a career in pharmaceutical, digital manufacturing and data-driven engineering sectors.

Continuous Direct Compression (CDC) is rapidly emerging as a preferred method for pharmaceutical tablet production. A central challenge is powder blending, where active pharmaceutical ingredients (APIs) must be uniformly mixed with excipients to ensure precise, consistent dosage and product quality. You will develop predictive computational models, validated using experiments and industrial data, to transform how pharmaceutical blending processes are designed and scaled. The project combines simulation, high-performance computing and industrially relevant experimentation, providing a unique opportunity to gain expertise that is highly sought after across pharmaceutical and advanced manufacturing industries.

This project is part of the EPSRC CDT in Process Industries: Net Zero. The successful PhD student will be co-supervised by academics from the Process Intensification Group at Newcastle University.

Number Of Awards

1

Start Date

1 October 2026

Award Duration

4 years

Award Closing Date

22 July 2026

The advert will close at midnight on 22 July 2026. Interviews will be conducted as applications are received and the position may be filled before the closing date.

Sponsor

EPSRC

Supervisors

Dr Colin Hare (colin.hare@newcastle.ac.uk)

Eligibility Criteria

You must have, or expect to gain, a minimum 2:1 Honours degree or international equivalent in a subject relevant to the proposed PhD project (usually chemical engineering or chemistry, but please get in touch if you think your qualification may be relevant). Enthusiasm for research, the ability to think and work independently, excellent analytical skills and strong verbal and written communication skills are also essential requirements. This studentship is available to home students only.

How To Apply

You must apply through the University’s Apply to Newcastle Portal. Once registered select ‘Create a Postgraduate Application’. Identify your programme of study via ‘Course Search’. Search for the ‘Course Title’ using the programme code: 8856F. Leave the 'Research Area' field blank. Select ‘PhD in Process Industries; Net Zero (PINZ)' as the programme of study. You will then need to provide the following information in the ‘Further Details’ section:

  • A ‘Personal Statement’ (this is mandatory) - upload a document or write a statement directly into the application form
  • The studentship code PINZ11-26 in the ‘Studentship/Partnership Reference’ field
  • Research Proposal - when asked how you are providing your research proposal, select ‘Write Proposal’, and enter the title of the research project from this advert. You do not need to upload a separate proposal.
  • Upload your CV

You must submit one application per studentship; you cannot apply for multiple studentships in one application. Find out more about the Admissions Process and Timeline for applications for PINZ CDT studentships at Newcastle University.

Contact Details

pinz.cdt@ncl.ac.uk

PhD Studentship - Process Industries: Net Zero - Predictive Modelling of Powder Blending in Con[...] in Newcastle upon Tyne employer: Emerging Scholars Council

Newcastle University is an exceptional employer, offering a vibrant academic environment that fosters innovation and collaboration. With a strong commitment to research excellence and professional development, employees benefit from access to cutting-edge resources and opportunities for growth in the field of implementation science. Located in a dynamic city known for its rich cultural heritage and supportive community, Newcastle University provides a unique setting for meaningful and impactful work.

Emerging Scholars Council

Contact Details:

Emerging Scholars Council Recruitment Team

We think you need these skills to ace PhD Studentship - Process Industries: Net Zero - Predictive Modelling of Powder Blending in Con[...] in Newcastle upon Tyne

Communication Skills
Problem-Solving Skills
Adaptability
Compassion
Caring for Others
Emotional Support
Flexibility