Research Fellow in Formal Verification - School of Computer Science - 106122 - Grade 7

University of Birmingham; Birmingham; On-site; GBP 36,636 - 46,049; Full time

Job summary

A prestigious educational institution in Birmingham is seeking a Research Fellow in Formal Verification. This role focuses on developing advanced machine learning algorithms for automated software verification and involves collaboration with experts in the field. Candidates should have a higher degree and proven publishing ability in AI or related fields. The position is full-time with a salary range of £36,636 to £46,049, offering a unique opportunity to advance in academic research.

Qualifications

• First degree in area of specialism.
• Proven ability to publish in relevant conferences and journals.
• Ability to assess and use resources effectively.

Responsibilities

• Develop advanced theory and machine learning algorithms for verification.
• Contribute to writing bids for research funding.
• Supervise students on research projects.

Skills

Proficiency in programming

Ability to publish in top-tier conferences

Experience presenting research findings

Education

Higher degree relevant to formal verification or machine learning

Tools

Machine learning software

Automated reasoning tools

Job description

Overview

Research Fellow in Formal Verification - School of Computer Science - 106122 - Grade 7. The role is with the University of Birmingham.

Position Details

• Location: University of Birmingham, Edgbaston, Birmingham UK
• Full-time starting salary: £36,636 to £46,049 with potential progression to £48,822
• Grade: 7
• Full Time, Fixed Term contract up to September 2026
• Closing date: 15 September 2025

Background

The School of Computer Science at the University of Birmingham is inviting applications for a Research Fellow position focused on Machine Learning for Automated Formal Verification. Machine learning has transformed programming, with code generation rapidly becoming standard practice. However, achieving formal assurance of software correctness remains a complex challenge. Seminal work in programming language semantics provides powerful frameworks for constructing correctness proofs, yet the standard symbolic methods face significant limitations in both expressivity and scalability. This project proposes novel techniques for constructing formal proofs of the correctness of software and hardware systems using machine learning. Recent advances in neural certificates—such as neural model checking and neural termination analysis—have shown promising results in this direction. The project aims to develop a comprehensive approach to software verification grounded in neural certificate technologies.

Role Summary

The Research Fellow will play a crucial role within the Neural Software Verification project, funded via an Amazon Research Award. They will work in close collaboration with Dr. Mirco Giacobbe (University of Birmingham) engaging in cutting-edge research in machine learning and automated reasoning for safe algorithmic systems. The Research Fellow will be responsible for developing advanced theory and machine learning algorithms for automated software verification. This role offers a unique opportunity to work at the forefront of formal methods and machine learning research, contributing to the foundational principles of how AI is applied to automated software and hardware verification.

Main Duties

• Develop advanced theory and machine learning algorithms for automated software verification
• Contribute to the research goals of the project through collaborative research, with guidance from mentors and a network of collaborators
• Contribute to writing bids for research funding
• Analyse and interpret data
• Develop new intellectual understanding through applied knowledge
• Disseminate research findings at conferences and seminars and contribute to academic publications
• Supervise students on research projects and provide guidance to PhD students where appropriate
• Contribute to developing new models, techniques and methods
• Undertake management/administration arising from research
• Contribute to Departmental/School research-related activities and administration
• Contribute to enterprise, business development and/or public engagement activities often under supervision of a project leader
• Address problems affecting achievement of research objectives and deadlines
• Promote equality and value 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 formal verification, automated reasoning, machine learning, or equivalent qualifications
• Proven ability to publish in top-tier conferences and journals in AI, computer-aided verification, automated reasoning, or quantum computing
• Experience presenting research findings at seminars and conferences and ability to communicate complex information clearly
• Proficiency in programming, with knowledge of (or willingness to learn) machine learning software, automated reasoning tools, or quantum simulation platforms
• Ability to assess resource requirements and use resources effectively
• Understanding of and ability to contribute to broader management/administration processes
• Contribute to planning and organizing the research programme and/or specific project
• Coordinate own work with others to avoid conflict or duplication of effort
• Knowledge of the Equality Act 2010 and ensuring equal and fair treatment of protected characteristics in day-to-day activity

Informal enquiries to Dr. Mirco Giacobbe, email: [e-mail]

We are committed to equality, diversity and inclusion. We hold Athena SWAN, Race Equality Charter and Disability Confident accreditations. We strive to create a fair and inclusive place to work and are committed to sustainability as part of our strategy. For more information, visit our website.