Job Description
The Mechanobiology Institute (MBI) at the National University of Singapore (NUS) is a leading multi-disciplinary institute devoted to developing new paradigms for understanding biological functions in health and diseases from the perspective of cell, tissue and organ mechanics/dynamics and mechano-signal transduction. The institute operates on a fully integrated open-lab philosophy, with an extensive infrastructure supported by core facilities dedicated to technology such as state-of-the-art light microscopy, nano- and micro- fabrication, and computing.
We are seeking a highly motivated, self-driven Postdoctoral Research Fellow to join the Collective Cell Dynamics in Mammalian Development and Reproduction Laboratory at MBI. The group investigates how collective cell behaviours emerge and contribute to biological functions in mammalian development and reproduction. It focuses on cellular mechano-chemical coupling in living tissues and aims to uncover the design principles of multicellular dynamical systems through interdisciplinary approaches that integrate advanced imaging, quantitative analysis, molecular and cellular biology, and animal models.
The selected candidate will investigate the regulation of the ovarian reserve and the spatiotemporal dynamics of ovarian follicles to determine how follicles and their surrounding cellular and tissue environments interact across space and time to influence follicle activation, growth, maintenance, and reproductive ageing. The project will focus on the visualisation and quantitative analysis of follicular behaviours in mouse ovarian tissue using advanced imaging techniques, as well as explore cellular metabolic states and energy-related signalling dynamics through label-free metabolic and biosensor-based live imaging.
The candidate will also develop and apply experimental and analytical approaches to study ovarian tissue dynamics, with opportunities to contribute creatively to the project's direction and priority access to a label-free metabolic imaging system for project-related experiments. Depending on the candidate's expertise and research interests, the work may involve live imaging, tissue and organ culture, quantitative image analysis, molecular and cellular assays, and the use of mouse models.
Candidates should demonstrate a strong passion for research, intellectual curiosity, and a creative, problem-solving mindset. They should be able to work independently and collaborate effectively within a diverse, interdisciplinary team.
Key Responsibilities
- Develop and apply imaging-based approaches to study the spatiotemporal behaviour of follicles in ovarian tissue
- Apply label-free metabolic imaging and biosensor-based imaging to investigate cellular metabolic states and energy-related signalling in ovarian tissue
- Perform quantitative image and data analysis and integrate imaging findings with molecular and cellular measurements
- Maintain clear experimental records, analyse and interpret results, and communicate findings through presentations and publications
- Collaborate with researchers from complementary experimental and quantitative disciplines
- Contribute to the training and mentoring of junior laboratory members, where appropriate
Requirements
- PhD in life sciences, bioengineering, biomedicine, or a related field
- Experience in microscopy, imaging, cell and tissue biology, or quantitative biological research
- Fundamental knowledge and practical skills in molecular biology and cell or tissue culture
- Ability to work independently, manage research projects, and troubleshoot experimental challenges
- Excellent communication, organisational, and teamwork skills
Preferred Qualifications
- Experience in mouse handling, mouse models, or murine tissue collection and experimentation is strongly encouraged
- Experience with live-tissue, intravital, confocal, multiphoton, or other advanced microscopy techniques would be advantageous
- Prior research experience in ovarian biology, folliculogenesis, reproductive ageing, developmental biology, or tissue dynamics would be beneficial
To Apply
Interested applicants should include the following in their online application a full CV with a list of publications (where applicable) and the names and contacts of two academic references. We regret that only shortlisted candidates will be notified.
