Research Fellow (Ecology/Biogeochemistry/Earth/Soil Science/Environmental Science/Hydrology/Computer Science)

Nanyang Technological University · Singapore

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The Asian School of the Environment (ASE) at Nanyang Technological University (NTU) is an interdisciplinary school that will be a world leader in environmental research focused on Asian environmental challenges. The ASE integrates Earth and environmental sciences to build an understanding of our planet and environment and to address key issues of environmental sustainability and its impact on society.

For more details, please view https://www.ntu.edu.sg/ase.

We are looking for 1 Research Fellows to join the research team led by Nanyang Assistant Professor Feng Tao in computational ecology, starting as early as possible. The role will focus on developing a process-guided and AI-assisted soil community foundation model for natural climate solutions. Candidates with prior experience in process-based modeling/data analytics/deep learning are preferred.

Key Responsibilities:

Strong candidates should take the lead of at least one of the following responsibilities:

• Soil organic carbon model development and optimization, focusing on microbial processes and stoichiometry dynamics
• Crop model development and optimization, focusing on pore-to-rhizosphere scale nutrient uptake and yield dynamics
• Global soil meta-databases collection, integration, and synthesis
• Earth system model new module integration, scenario simulations, and prognostics analyses
• Physics-informed deep learning/hybrid modeling/reasoning AI algorithm development and optimization

Job Requirements:

• PhD qualification degree in ecology, biogeochemistry, Earth/soil science, environmental science, hydrology, computer science, or related field
• Familiarity with soil carbon/element cycles
• Prior experience in at least one of the following fields: process-based model development, Earth system model simulation and analyses, data assimilation, large-scale data collection and synthesis, high performance computing, and deep learning
• Strong academic writing and communication skills
• Prior involvement in research projects, evidence of publishing in peer-reviewed journals or presenting at conferences are preferred.

Interested candidates should submit the following documents:

• A cover letter detailing research interests and relevant experience.
• A current CV, including contact information for two references.
• One representative publication (if applicable)

We regret to inform that only shortlisted candidates will be notified.

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