Senior Scientist Modelling & Quantification

0 years

0 Lacs

Posted:1 month ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

Job Overview:


Desired Qualification

• 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 (8-12 yrs)

• Strong/Prior experience with crop models, biogeochemical models and environmental technologies data analysis tools and resources is essential (8-12 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

Key Responsibilities & duties

•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

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