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Arkansas State University - Jonesboro, AR

posted 3 months ago

Full-time - Entry Level
Onsite - Jonesboro, AR
Educational Services

About the position

The Data Scientist position at Arkansas State University focuses on supporting research projects aimed at improving crop management practices in the Lower Mississippi River Delta. The role involves providing advanced analytical support, technical expertise, and process-based modeling, specifically as a greenhouse gas (GHG) flux modeler in collaboration with USDA-ARS researchers. The position requires the development of executable programs for GHG flux modeling and user feedback assessment to enhance the model's effectiveness.

Responsibilities

  • Design and develop complex scientific modeling applications to automate the computation of atmospheric gas emissions in agriculture.
  • Apply advanced computational modeling, data analytics, machine learning, and scientific visualization to estimate carbon footprint in irrigated crops.
  • Refine software for calculation and modeling of greenhouse gas emissions from agronomic crops.
  • Conduct data analysis and inferential statistics to evaluate the utility of GHG software for public users.
  • Create and maintain a website for the model.

Requirements

  • An earned PhD in Engineering Science, Computer Science, Computer Engineering, Software Engineering, Data Science, or related fields.
  • Expert in C/C++, Python, and JavaScript.
  • Proficient in data science and visualization tools such as pandas, scipy, plotly, dash, SALib, seaborn.
  • Experience with artificial intelligence and machine learning frameworks such as scikit-learn and Keras.
  • Knowledge of GIS image analysis tools such as ArcGIS and web mapping tools like OpenLayers, Leaflet, and Mapserver.

Nice-to-haves

  • Experience in handling large datasets.
  • Experience in working on greenhouse gas emission datasets.

Benefits

  • Full-time employment status with a proposed salary range commensurate with experience.
  • Remote work flexibility with no on-site time required.
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