Staff Software Engineer, Build Systems

Job description Did you know that insects could be central to a more sustainable future?

They can upcycle organic waste into high-value protein and fat, support biological control, and provide low-carbon alternatives to conventional animal feed.

Yet the growth of insect-based industries is limited by one major bottleneck: how to design diets that are affordable, environmentally responsible, and biologically effec tive.

Diets typically account for over half of production costs, and even small changes in composition can alter growth rates, survival, and nutrient conversion.

Despite decades of research, diet formulation remains largely trial-and-error.

This project uses cutting-edge AI to transform diet design into a data-driven, scalable process.

You will develop an automated pipeline for gathering, extracting, and structuring knowledge from scientific literature and online repositories, generating the first comprehensive database linking diet composition to insect performance and environmental footprint.

Building on this, you will train multi-modal transformers to predict multi-trait responses and to design diets that balance growth, cost, and carbon impact.

Finally, working with our industry partner NASEKOMO®, you will test AI-designed diets in large-scale black soldier fly rearing trials providing rare experience in deploying Generative Active Learning models directly into industrial biotechnology.

This PhD offers outstanding interdisciplinary training.

You will gain skills in:

• Generative AI (Diffusion Models), Multi-Modal Deep Learning, Explainable AI and Conformal

• Prediction.

• Natural language processing (SciBERT) and automated data extraction.

• Sustainability science and life-cycle assessment.

• Experimental design and validation in real industrial environments

You will be co-supervised by specialists in AI, insect biology, and sustainability assessment, working within a collaborative team spanning academia and industry.

For students excited by real-world impact, this project offers a unique opportunity to apply AI to one of the most urgent sustainability challenges in the agri-food sector and to help shape the future of sustainable protein systems.

To apply, please visit this webpage: https://www.sustain-cdt.ai/apply

Funding

Honours degree (minimum 2:1) in Computer Science, Informatics, or Mathematics with strong expertise in Python and PyTorch and/or R, as well as general programming and computer systems, e.g., using Linux, etc.

Alternatively, students can have a Honours degree (2:1) in Biological Sciences, Agricultural Sciences, or any other related area but should be able to demonstrate ability to program and show strong interest in learning machine learning and AI.

It is essential that the PhD student is self-driven, curious, interested in working across disciplines and exploring new areas, as well as eager to work as part of an interdisciplinary team.

The student will be expected to engage with their peers and other academic staff, get involved in departmental events and seminars, and show enthusiasm for public/policy engagement activities.

Desirable:

• a master’s degree in AI, Machine Learning, Biological Sciences or Agri-Food Systems with a strong component of AI or computing

• BSc in a relevant subject

Our fully-funded studentship package includes:

• All PhD tuition fees paid.

• A tax-free stipend at UKRI rates to cover living costs.

• A Research Training Support Grant (RTSG) of £3,000 each year to support travel, training and consumables costs (up to £12,000 in total).

• Additional funding to support outreach and dissemination, attendance at summer schools, research events, and development projects.

Application Deadline

12pm (midday) GMT Friday, 20th March 2026

Enquiries

SUSTAIN@lincoln.ac.uk

Application Webpage

https://www.sustain-cdt.ai/apply Show full description Report this listing Loading