PhD in insect phenomics: Real-time AI and computer vision for enhanced black soldier fly production
2 weeks ago
Title:
PhD in insect phenomics: Real-time AI and computer vision for enhanced black soldier fly production
Research area and project description:
We are seeking a highly motivated PhD student to join a 3-year PhD position within the SmartLarva project, funded by Innovation Fund Denmark's Grand Solutions Grant. The project aims to develop cutting-edge computer vision and AI tools for real-time monitoring and analysis of black soldier fly larval development, thereby revolutionizing sustainable insect production.
The urgent need for sustainable protein sources is driving rapid growth in insect farming, particularly black soldier fly (BSF) production. BSF farming converts organic waste into high-quality, protein-rich larvae with significantly lower environmental impact than conventional protein sources. However, the industry faces efficiency and scalability challenges due to limited technological solutions and biological insights. Current practices rely heavily on manual monitoring, which becomes increasingly inefficient as production scales up. Additionally, the lack of reliable phenotyping tools hinders the implementation of genetic improvements crucial for robust production.
The SmartLarva project aims to address these challenges by developing two innovative solutions: a distributed wireless in-crate vision system for tracking larval growth and behaviour, and a phenotyping platform for real-time ranking of candidates for selective breeding and larval sex classification. The PhD project will focus on:
- In-crate vision system development: Design and validate an automated, high-throughput imaging system that continuously monitors larval growth and behaviour under varying environmental conditions.
- Deep learning for phenotypic analysis: Develop and implement advanced deep learning models to analyse complex image data, extract critical larval traits, and predict optimal harvest timings.
- AI-driven data integration: Integrate multi-sensor data streams with AI algorithms to create a comprehensive, real-time decision support system that enhances selective breeding and production efficiency.
This research will explore exciting questions about applied computer vision in challenging biological environments, real-time monitoring of small organisms, and the use of AI for phenotypic trait identification, providing valuable insights for sustainable food production systems.
Your research will be conducted at the Center for Quantitative Genetics and Genomics (QGG) at Aarhus University, an environment that nurtures dynamic, inclusive, and multidisciplinary collaboration where innovative ideas flourish. Based at the university's main campus - a prestigious institution in a vibrant, student-friendly city - you will work closely with the Digital Approaches for Sustainable Agriculture and Insect Production group. In addition, you will collaborate with leading private sector partners, including Enorm BioFactory, Better Insect Solutions (BIS), and SKOV A/S, ensuring that your research delivers direct and impactful real-world applications.
Candidates will be evaluated based on their CV, a motivation statement, and reference letters. Shortlisted candidates will be invited for an interview (either online or in person). The top candidate will be offered the PhD position.
Why apply?
- Be at the forefront of integrating AI and computer vision with sustainable food production
- Lead original research addressing real-world challenges in a rapidly growing industry
- Work in a collaborative environment with both academic and industry partners
- Gain experience with cutting-edge technologies applied to biological systems.
Project description: For technical reasons, you must upload a project description. Please simply copy the project description above and upload it as a PDF in the application.
Qualifications and specific competences:
Applicants to the PhD position must have a master's degree in data science, computer and electronic engineering, photonics, or a closely related field, preferably with experience in applying these technologies in biological research settings.
Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Department of Quantitative Genetics and Genomics, C. F. Møllers Allé 3, 8000 Aarhus C., Denmark.
Contacts:
Applicants seeking further information regarding the PhD position are invited to contact:
- Mogens Sandø Lund, mogens.lund@qgg.au.dk (main supervisor)
- Grum Gebreyesus, grum.gebreyesus@qgg.au.dk (co-supervisor)
For information about application requirements and mandatory attachments, please see our application guide. If answers cannot be found there, please contact:
- admission.gradschool.tech@au.dk
How to apply:
Please follow this link to submit your application.
Application deadline is 21 April 2025 at 23:59 CEST.
Preferred starting date is 01 August 2025
Please note:
- Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be taken into account.
- The programme committee may request further information or invite the applicant to attend an interview.
- Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
Aarhus University's ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.
Please note in your application that you found the job at Jobindex
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