Postdoc: AI-Driven Moss Carder Bee Conservation

University of Cambridge; Cambridge; On-site; GBP 34,000 - 42,000; Full time

Job summary

The University of Cambridge invites applications for a postdoctoral researcher to lead a 1-year project bridging machine learning for species identification and real-world insect conservation, focusing on the moss carder bee (Bombus muscorum), a vulnerable species.

Based in the Brown Lab, Department of Zoology, you will develop a visual recognition tool using ML and DNA barcoded photos, conduct fieldwork, and coordinate scientists and volunteers from the Bumblebee Conservation Trust,

Qualifications

• PhD in a relevant field with a strong research track record.
• Experience with machine learning for image analysis and species identification.
• Ability to conduct fieldwork and coordinate multiple collaborators and volunteers.

Responsibilities

• Build and evaluate a visual recognition tool for Moss carder bee (Bombus muscorum).
• Conduct fieldwork and coordinate scientists and volunteers from the Bumblebee Conservation Trust.
• Contribute to training new team members and supervise students and postdocs.
• Engage in general project management and public engagement activities.

Skills

Machine learning

DNA barcoding

Fieldwork

Coordination

Public engagement

Education

PhD in a relevant field

Tools

Python

DNA barcoding tools

Image analysis tools

Job description

The University of Cambridge invites applications for a postdoctoral researcher to lead a 1-year project bridging machine learning for species identification and real-world insect conservation, focusing on the moss carder bee (Bombus muscorum), a vulnerable species.

Based in the Brown Lab, Department of Zoology, you will develop a visual recognition tool using ML and DNA barcoded photos, conduct fieldwork, and coordinate scientists and volunteers from the Bumblebee Conservation Trust,