Research Assistant in Developmental Mechanics

We are looking for a full-time Research Assistant working closely with Dr Fengtong Ji in Dr Fengzhu Xiong's lab at the Gurdon Institute, University of Cambridge. The successful candidate will be involved in studies of cell dynamics and tissue morphogenesis during embryo development using nano-engineering, cellular and molecular approaches., Cell-type transition and tissue property changes widely exist in the development of normal and malignant tissues. Using chick embryo as the model system, we are investigating the mechanical cues regulating tissue organisation and developing innovative nanorobotic tools to explore the fundamental mechanisms through our unique homemade devices, in addition to ample resources from the core facilities at Gurdon Institute and other departments at Cambridge., Main duties include: Conduct wet-lab experiments; Acquire and process data; Prepare reagents and samples; Program and debug codes for analysis; Optimise protocols; Coordinate with the PI and Lab Manager; Support other projects if requested; Participate in regular group meetings and other group activities.

As a member of an interdisciplinary team, the candidate will have the opportunity to receive training in a variety of techniques including molecular biology, embryology, nanorobotics, imaging, computation and biophysics. They will have the opportunity to develop independent projects after gaining adequate experience. Moreover, they will also receive support if they wish to participate in career development activities including appropriate professional courses while in the role. This is an excellent opportunity for someone enthusiastic about learning new techniques, proactive in supporting the research and self-motivated in advancing science.

It is essential that the candidate has delicate operational abilities in wet-lab experiments (such as micromanipulation), detail-oriented research insight and exceptional record-keeping working habits. The experiments in this project need to be well-scheduled and timely conducted as planned.

The successful applicant will have strong organisational and communication skills and excellent problem-solving skills. Experience and a good understanding of working in research labs are required. Prior lab experience related to active matter, surface modification, image analysis (e.g., using Python programming) and confocal microscopy is desirable.