Research Fellow – School of Computer Science – 107477 – Grade 7 Full-time

Job Posting

School of Computer Science

Location: University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £36,636 to £46,049 with potential progression once in post to £48,822

Grade: 7

Full Time, Fixed Term contract up to November 2027

Closing date: 1st July 2026

Background

The School of Computer Science at the University of Birmingham is inviting applications for a Research Fellow on Physics-informed Data-driven Control and AI Methods for Safe AI with focus on modelling for AI-Enabled Biopharmaceutical Manufacturing.

As systems and processes increasingly integrate process modelling and data-driven methods, ensuring their safety and alignment with expected outcomes is essential. In particular, there is a growing interest in integrating mathematical models with machine learning algorithms for biopharmaceutical processes, which emphasises the needs for safe control and robustness of the deployed AI technologies.

Role Summary

The Research Fellow will play a crucial role within the Safeguarded AI project, funded by ARIA (Advanced Research and Invention Agency). As a key contributor, the research fellow will work in close collaboration with Dr. Leonardo Stella and Dr. Mirco Giacobbe, as part of an industrial collaboration with AstraZeneca, Cambridge UK, and will engage in cutting-edge research in data-driven control and AI safety, formal verification, dynamical systems and mathematical modelling for the analysis of biopharmaceutical processes.

In this role, you will develop mathematical models and algorithms for the analysis of biopharmaceutical manufacturing processes.

The goal is to enable the application of safety assurance that characterises the mathematical description of biopharmaceutical processes with physics-informed data-driven approaches.

This project offers an opportunity to be at the forefront of interdisciplinary research, making a significant contribution to the fundamental principles of physics-informed data-driven control and AI methods for safe AI in the biopharmaceutical manufacturing sector.

Main Duties

• Contribute to the research goals of the project through collaborative research, with guidance from mentors and a strong network of collaborators.
• Contribute to writing bids for research funding.
• Analyse and interpret data.
• Apply knowledge in a way which develops new intellectual understanding.
• Disseminate research findings at conferences and seminars and contribute to academic publications.
• Supervise students on research-related work and provide guidance to PhD students where appropriate to the discipline.
• Contribute to developing new models, techniques and methods.
• Undertake management/administration arising from research.
• Contribute to Departmental/School research-related activities and research-related administration.
• Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University, often under supervision of a project leader.
• Deal with problems that may affect the achievement of research objectives and deadlines.
• Promotes equality and values diversity acting as a role model and fostering an inclusive working culture.

This position is ideal for candidates eager to pursue a career in academia or advanced research, and who are encouraged to contribute their own independent research ideas to the project.

Person Specification

• First degree in area of specialism and normally, a higher degree relevant to control theory, formal verification, dynamical systems, stochastic analysis, statistics or equivalent qualifications
• Proven ability to publish in top-tier conferences and journals in machine learning, automatic control, bioinformatics.
• Experience presenting research findings at seminars and conferences and ability to communicate complex information clearly.
• Proficiency in programming, with expertise of machine learning software and formal verification platforms.
• Ability to assess resource requirements and use resources effectively.
• Understanding of and ability to contribute to broader management/administration processes.
• Contribute to the planning and organising of the research programme and/or specific research project.
• Coordinate own work with others to avoid conflict or duplication of effort.
• Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day-to-day activity in own area that those with protected characteristics are treated equally and fairly.