Two Postdoctoral Research Positions in Computer Vision and Deep Learning for Biodiversity Monitoring

Postdoctoral Positions in Image Recognition and Computer Vision for Ecological Monitoring

Department of Ecoscience, Aarhus University

The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to advance our research in image recognition, computer vision, and deep learning applied to ecological monitoring. The successful candidates will develop analysis pipelines and implement next-generation sensors for automated insect monitoring across Europe as part of ongoing EU Horizon Europe projects.

Position Details

• Duration: 2-year postdoctoral positions
• Start Date: June 1, 2026, or as soon as possible thereafter

Research Focus

Insect declines represent an urgent ecological and societal challenge requiring innovative approaches to biodiversity data collection and interpretation. We are expanding our research group working on image-based methods for large-scale biodiversity monitoring, seeking candidates eager to push the boundaries of automated ecological data collection.

These positions focus on improving detection and classification performance of deep learning models applied to millions of images collected in European monitoring programs.

Key Responsibilities

• Quantify insect abundance, diversity, and biomass from image data
• Validate and benchmark model outputs
• Develop efficient pipelines for localizing insects on simple backgrounds and complex natural scenes
• Improve taxonomic classification using hierarchical classification schemes and anomaly-detection methods
• Test and validate next-generation insect camera traps with on-device computing for real-time detection and classification
• Collaborate in interdisciplinary teams spanning ecology, computer science, engineering, and biodiversity monitoring
• Communicate results and work closely with international partners and stakeholders

These positions will contribute to developing scalable image-based monitoring tools capable of addressing fundamental questions in biodiversity and conservation.

Required Qualifications

• PhD in computer science, biology, software engineering, or related field
• Strong proficiency in Python with experience in modern deep learning frameworks
• Solid understanding of applied statistics
• Experience working with large-scale image datasets
• Excellent English communication skills

Desirable Qualifications

• Experience with ecological datasets or biodiversity applications
• Experience with hardware integration, embedded systems, or edge computing
• Track record of publishing technical or interdisciplinary work in relevant scientific journals
• Motivation to work in international and interdisciplinary research environments

About the Department

The Department of Ecoscience conducts world-class research in aquatic and terrestrial biology and ecology, arctic environment and ecosystems, and biodiversity and conservation biology. We employ approximately 275 academic and technical staff plus many PhD students, offering a vibrant and informal research environment with longstanding traditions for collaboration with elite international university partners.

What We Offer

Join a dynamic research environment emphasizing teamwork and close working relationships. The department maintains a strong work-life balance policy and actively promotes gender and age diversity. English is widely spoken, and we welcome international applicants. We offer comprehensive services for international researchers and accompanying families, including relocation services and career counseling for partners.

Location

C. F. Møllers Allé 8, DK-8000 Aarhus C, Denmark

Application Deadline

March 3, 2026

Application Requirements

Applications must be in English and include:

• Curriculum vitae
• Degree certificates
• Complete list of publications
• Statement of future research plans
• Information about research activities
• Teaching portfolio and verified teaching experience (if applicable)

Applications must be submitted via Aarhus University's online recruitment system. A shortlisting process will be used, and all applicants will be notified whether their applications proceed to expert assessment committee evaluation.

Aarhus University is committed to fostering an attractive and inspiring workplace for all, valuing equality and diversity as assets. We encourage applicants to specify any periods of research leave to ensure fair evaluation of scientific productivity.