Quantitative Research Associate Alt Carbon

14.0 - 18.0 years

0 Lacs

karnataka

On-site

As a Quantitative Research Associate at Alt Carbon, you will be an integral part of our Science & Modeling team at Shonku Labs located in Bangalore (IISc Campus) or through a hybrid working model. With a rich experience of 14 years, you will join our pioneering efforts in Carbon Removal (CDR) to combat climate change by combining science, technology, and tradition. Alt Carbon, founded by Shrey and Sparsh Agarwal, focuses on Carbon Dioxide Removal (CDR) through Enhanced Rock Weathering (ERW) to address historic emissions in the atmosphere. Our operations in Darjeeling's heritage tea estates exemplify our commitment to climate action and sustainability. Your role will involve designing and validating mathematical models related to mineral weathering, geochemical fluxes, and carbon sequestration. You will work collaboratively with various teams to transform complex physical data into accurate CDR figures and contribute to the development of registry-grade carbon accounting methods. Key Responsibilities: - Designing and validating mathematical models for mineral weathering and carbon sequestration - Conducting uncertainty quantification and error analysis - Building Monte Carlo simulations and stochastic models for carbon accounting - Analyzing datasets from lab, field, and satellite sources - Supporting sampling optimization strategies - Collaborating with product and software teams for scientific integration - Contributing to technical publications and whitepapers Qualifications: - Bachelor's or Master's degree in Mathematics, Applied Statistics, Data Science, Physics, Environmental Engineering, Computational Sciences, or related fields - Experience in statistical modeling, error analysis, and simulation methods - Proficiency in Python or R for data analysis - Ability to understand and replicate scientific models and equations - Bonus: Familiarity with spatial data, environmental datasets, or climate modeling As a quantitative thinker, you will thrive in the complexity of real-world data, treating uncertainty as a solvable challenge. Your rigorous approach to modeling and data analysis will play a crucial role in influencing public policy, climate impact, and planetary systems. Join us in shaping the future of carbon removal science and making a meaningful impact on global climate change efforts.,

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