Research Associate/Senior Research Associate (Genetic Improvement for Emergent Systems)

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Research Associate/Senior Research Associate (Genetic Improvement for Emergent Systems)

School of Computing and Communications
Salary: £36,386 to £42,155
Closing Date: Friday 28 October 2022
Interview Date: Wednesday 16 November 2022
Reference: 0896-22

Job Title: Research Associate/Senior Research Associate (Genetic Improvement for Emergent Systems)

Department: School of Computing and Communications

Salary: £28,756 - £40,927

Closing Date:

We are seeking a post-doctoral researcher to work on the Leverhulme Research Grant project “Bio-Enhanced Genetic Improvement for Emergent Software Systems”.

This project will explore how live software systems can improve their own performance by capturing runtime data, replaying that data offline, and automatically synthesising improved software components for re-injection into the live system. The research is built atop the concept of emergent software systems which self-assemble from a pool of building blocks, and continuously re-assemble themselves using alternative building blocks over time. This project will examine genetic improvement (GI) using novel phylogenetic and meta-population theory to enhance genetic search effectiveness, and with the help of a PhD candidate will also examine how live genetic improvement fits into existing software engineering processes.

Key Research Directions

A prototype GI framework has already been developed, as has the underlying emergent software systems approach. Key research directions will include:

1. Creation of a phylogenetic GI system for source code, able to automatically capture and analyse phylogenetic data to understand changes in fitness between generations relative to the mutations and crossovers that were applied over a given time period. Using continuous time-series results of phylogenetic analysis, you will then implement a connected real-time machine learning layer which directs the GI process to use mutation groups and crossover approaches that are known to be of high utility for individuals of that type from past experience.

2. Based on meta-population theory in biology, you will examine the deliberate curation and storage of multiple distinct populations over time, all designed to improve the same initial software building block or group of blocks. We will use this approach to (i) increase the overall amount of genetic material available to bridge neutral areas of program space, and (ii) evolve for evolvability by maintaining a set of populations whose members represent high-utility jumping off points for useful variations derived from branching GI processes.

Besides these directions, we also welcome your input and creativity in complementary research which fits within the project – we actively encourage self-led research alongside project deliverables.

Experience Needed

The ideal candidate will have knowledge of genetic improvement. We are also able to offer guidance and support on this field, however, so general computer science researchers are welcome. The candidate will be expected to implement and test algorithms throughout the project and so good programming skills are desirable, as is the ability to run large-scale experiments on Linux clusters.


You will join a team of three people working on inter-related research objectives for this project, and will join a wider research group of systems researchers working in operating systems, distributed systems, and self-adaptive software.

You will join us on an indefinite contract. However, the role remains contingent on external funding which, for this position, ends 15th July 2026

If you have informal enquiries please contact Dr Barry Porter by email at:

We welcome applications from people in all diversity groups.

Lancaster University – ensuring equality of opportunity and celebrating diversity

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Further details:
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In your application, please refer to and reference JobID 2362237.