昆虫行为与精准农业博士项目：黑兵虫幼虫对环境应的反应

该博士项目旨在研究黑兵蝇幼虫如何因不同的饲养条件而表现出不同的行为反应，以及这些反应与生长、存活及生产性能之间的关系。研究采用先进的相机传感器技术，并与工程团队合作，以分析数据并优化昆虫养殖策略。

Project: Insect production is gaining importance as a way to convert organic side streams into valuable resources for food and feed. Black soldier fly (BSF, Hermetia illucens ) larvae are particularly promising because of their ability to transform a wide range of organic materials into nutrient-rich biomass containing proteins and fats. However, successful insect production requires a better understanding of how rearing conditions influence insect biology, behaviour and production performance. How do larvae respond to environmental variation? Can behavioural patterns help us understand their responses to challenging conditions and identify opportunities to improve rearing strategies? This PhD position is part of EntoBOOST , a project funded by the Research Foundation – Flanders (FWO). EntoBOOST brings together researchers from KU Leuven, Ghent University, the University of Antwerp, the University of Insubria in Italy, Inagro and Thomas More. The project aims to deepen our understanding of insect physiology, biology and behaviour to improve rearing strategies and support the production of safe, high-quality insect-based products with desirable biological and nutritional properties. Your PhD will address a central question within the project: How do black soldier fly larvae respond behaviourally to different rearing conditions, and how are these responses related to larval growth, survival and production performance? To investigate this, you will study larval behaviour using an advanced camera-based sensor platform already developed and operational within the research team. The platform combines high-resolution RGB imaging, visible and near-infrared multispectral imaging, and thermal imaging. These measurements will be complemented by gas-emission monitoring, including carbon dioxide, ammonia, nitrous oxide and methane, and by conventional rearing parameters such as larval growth and survival, substrate humidity, pH and composition. Your role You will work alongside a PhD researcher with an engineering background who continues to develop the sensor hardware and computer-vision algorithms used to extract movement and behavioural information from the images. Your primary focus will be the biological research: translating research questions into experiments, analysing behavioural data and interpreting the results in relation to environmental conditions, larval physiology and production performance. You will take ownership of the biological questions and statistical analysis while working closely with the engineering team to understand how sensor data are generated and how they can be used to answer those questions. Previous experience with computer vision is not required; curiosity about the technology and a willingness to learn are what matter. What will you do? Design and conduct experiments: develop and implement rearing experiments to investigate how different environmental and stress-linked conditions affect larval behaviour and production performance. Analyse behavioural data: work with the engineering team to extract meaningful behavioural features from camera-based sensor data and analyse behavioural time series. Connect behaviour to production: use statistical modelling to investigate relationships between behavioural patterns, environmental conditions, growth and survival. Investigate physiological responses: collaborate with researchers at the University of Antwerp to link behavioural observations to metabolic markers associated with stress. Communicate your findings: publish your results in international peer-reviewed journals and present your research at scientific conferences, contributing to the development of precision insect farming. You will be supported by KU Leuven experts in insect production and processing and livestock technology. Experiments will take place at the SymBIOnt Insect Pilot Plant of KU Leuven and Thomas More in Geel, as well as at Inagro's insect-rearing facilities. At the Toxicological Centre of the University of Antwerp, a fellow PhD researcher is developing and validating a metabolomics platform to identify biomarkers associated with stress in black soldier fly larvae. By combining your behavioural research with this work, you will help build a more comprehensive understanding of the biological responses of larvae to challenging rearing conditions. Ultimately, a better understanding of these responses can help identify opportunities to optimize rearing strategies, improve production efficiency and, in the longer term, contribute to production systems that better account for insect welfare.

Profile: We are looking for a curious and motivated PhD candidate who enjoys asking biological questions, working with data and collaborating across disciplines. You: Hold a Master's degree in biology, biosciences, bioscience engineering, animal sciences or an equivalent field. Candidates with a Master's degree in data science and a strong interest in biology are also encouraged to apply. Have a strong interest in animal behaviour (ethology), insect biology and the relationship between environmental conditions and biological responses. Are eager to investigate how rearing conditions influence larval behaviour, physiology and production performance. Enjoy working with data and are motivated to take responsibility for the statistical analysis and interpretation of your experiments. Are interested in how sensor technology and data analysis can advance biological research, and are willing to learn the basic principles of computer vision in collaboration with the engineering team. Have a critical, analytical, creative and innovative mindset. Have good written and oral communication skills in English. Enjoy working in an international, multidisciplinary research environment and collaborating with researchers from different backgrounds. The following experience is an advantage, but not a requirement: Insect rearing or entomological research, particularly involving black soldier fly larvae. Designing and conducting behavioural or animal experiments. Statistical analysis, including mixed-effects models, multivariate analysis or time-series analysis. Scientific data processing using R, Python, MATLAB or equivalent software. Experience with computer vision and machine learning. Eligibility condition: To be eligible for this position, you must hold a Master's degree with at least distinction, obtained within the last three years at a university in the European Economic Area (EEA).

录取条件： 我们提供一个全职博士研究生岗位，并给予具有竞争力的薪资待遇，时长为四年，希望能尽快开始招聘。 您将参与一个包含操作型传感器平台的多学科研究项目，并能够使用试点规模的昆虫饲养设施。这使您能够从一开始就专注于生物学研究问题，同时还能受益于工程学、昆虫生物学和代谢组学领域研究人员的紧密合作。 您可以预期： 实践性研究：利用专门的昆虫饲养与传感器设施进行实验设计与实施。 跨学科合作：将在多个研究机构与生物学家、工程师及研究人员密切合作。 科学发展：接受指导与培训，以提升研究能力并完成博士学位。 国际交流机会：可在会议中展示研究成果，发表科学论文，并构建专业人脉。 博士培养：需注册进入比利时荷语鲁汶大学的Arenberg博士学院，该学院提供涵盖科学与可迁移技能的综合性课程。 您将加入一个年轻、充满活力且跨领域的团队，该团队将在您的博士研究过程中为您提供全面支持。您的主要工作地点为比利时荷语鲁汶大学吉尔校区。无需掌握荷兰语。 昆虫生产与加工研究小组网站 畜牧技术研究小组网站

感兴趣？ 您可通过在线申请工具于2026年11月13日之前提交申请以参与此职位。 比利时荷语鲁汶大学致力于营造包容、尊重且安全的社会环境。我们将个人与群体的多样性视为一种优势。开放的对话与不同的观点是构建雄心勃勃的研究与教育环境的关键。在追求平等机会的承诺中，我们认识到历史不平等所带来的后果。我们不接受基于性别认同与表达、性取向、年龄、种族或民族背景、肤色、宗教与哲学差异、神经多样性、就业障碍、健康或社会经济状况等任何形式的歧视。 关于入学资格或支持措施的相关问题，我们愿通过此电子邮件地址为您提供帮助。 求职申请流程： 工作条件 职业机会 申请此职位