Greenhouse Gas Emissions Modelling Scientist
Our organization is seeking a highly motivated and data-savvy Scientist to join our
modelling team. This role is a unique opportunity to contribute to groundbreaking
research on quantifying carbon sequestration and greenhouse gas (GHG) emissions
from agriculture, in the Indian context.
Unveiling the Carbon Footprint: Research and Models Evaluation
• Explore biogeochemical models for quantification of GHG emissions from conventional
and improved agricultural practices.
• Analyze the strengths, weaknesses, and data requirements for each tool/model.
• Develop model/tool specific databases of of data parameters. This database will help
in designing our data collection exercises.
• Analyze (along with team) the suitability and applicability of these tools and models for
diverse geographical regions within India.
• Critically evaluate the strengths, weaknesses, and data requirements of each explored
model.
• Develop GHG Data analytics across models for several regenerative practices,
focusing on national and international emission reduction targets, environmental
impacts, enhanced soil health and fertility, improved water use efficiency, potential
yield improvement (if applicable), reduction in soil tillage practices, and improved
fertilizer management and burning practices.
• Develop comprehensive reports/templates comparing and contrasting various GHG
emission quantification tools and biogeochemical models.
• Recommend the most appropriate tools/models based on the team's specific needs.
• Develop clear and user-friendly spreadsheets for each explored tools/models.
• These spreadsheets will help the team for assessment of data needs for each
tool/model.
Credentials and Experience background:
• PhD (Environmental Engineering, Bioengineering, Natural Sciences, Agricultural
Sciences, Environmental Sciences/Tech, or a closely related field.
• Strong research skills and experience and the ability to critically evaluate scientific
literature and technical documentation (1-2 yrs)
• Strong/Prior experience with crop models, biogeochemical models and environmental
technologies data analysis tools and resources is essential (1-2 yrs)
• Strong knowledge in Agronomy is essential
• Strong knowledge in Biostatistics
• Excellent analytical and problem-solving skills – a natural-born problem cracker!
• Proficiency in data analysis tools and MS Office Suite.
• Familiarity with data science concepts is a significant advantage.