Research Fellow (Coral Climate Resilience)

About the role

The Earth Observatory of Singapore (EOS) at Nanyang Technological University (NTU) conducts research on climate and environmental change, with a strong focus on Southeast Asia. Its Coral Reef Eco-Geomorphology Group studies tropical coral reef biodiversity, ecological function and resilience using field ecology and quantitative analysis. It is seeking a Research Fellow in Coral Climate Resilience for an initial 12-month appointment, with potential extension depending on project needs and funding. The Fellow will study coral reef biodiversity, macroecological patterns and responses to marine heatwaves, bleaching and other environmental stressors across Southeast Asia.

Key responsibilities

• Lead research and publications on coral reef ecology, biodiversity, climate-change impacts and ecosystem resilience.
• Analyse large regional benthic and environmental datasets to identify patterns and drivers of change.
• Develop robust statistical and predictive approaches, including multivariate, hierarchical or Bayesian modelling.
• Plan and conduct regional scientific-diving fieldwork and collaborate with local research partners.
• Assess coral bleaching, reef-community dynamics and ecological indicators of vulnerability and recovery.
• Lead manuscripts, reports and presentations, and contribute to mentoring, data quality and collaborative group activities.

Required profile

• PhD in marine biology, ecology, evolutionary biology, environmental science or a related discipline.
• Strong publication record for the career stage in coral reef ecology, macroecology, climate-change biology or related fields.
• Experience with coral reef field ecology, biodiversity surveys and interpretation of benthic or reef-community data.
• Advanced Open Water or equivalent diving qualification; scientific diving, Divemaster and first aid/CPR/O2 training are advantageous.
• Excellent scientific writing, independent research and collaboration skills, and willingness to undertake regional fieldwork.

Required skills

• Strong quantitative skills in R/Python and experience analysing large ecological or environmental datasets.
• Experience with multivariate, hierarchical, Bayesian, spatial or predictive modelling is highly desirable.