Postdoctoral Research Associate

University of New Hampshire

3d

About The Position

This is a Post Doctoral position at the Ocean Process Analysis Laboratory at EOS. The hired person will work for Bror Jönsson to perform research within two of Jönsson’s grants. The work will entail modelling, data analysis, processing of satellite imagery, and other types of research. Tasks will also include writing and data management. The candidate will work on two funded projects that aim to model biological production in a Lagrangian frame using satellite data. The focus is mainly on the upwelling systems in Northern Gulf of Guinea. We will be working on three questions in the two projects: Improve coverage and resolution of satellite-derived properties using different instruments including geostationary weather satellites. Estimate primary and community production in a Lagrangian frame using velocity fields from a physical ocean model and satellite fields. Develop a data-constrained Lagrangian biogeochemical model using times series forecasting and machine learning. The Post Doc will focus on one or two of the questions depending on their expertise and interest.

Requirements

• Doctorate in Oceanography, Meteorology, Statistics, or similar field.
• Fluent in one or more programming languages (python, Julia, or possibly R)
• Able to perform or willing to learn geospatial analysis.
• Self-motivated
• Willing to pursue research objectives stated in the projects’ descriptions.
• Quantitively minded
• A background in Oceanography, Remote Sensing, Meteorology, or similar field.

Nice To Haves

• Comfortable to work in a Linux environment
• Experience with machine learning

Responsibilities

• Modelling
• Data analysis
• Processing of satellite imagery
• Writing
• Data management
• Improve coverage and resolution of satellite-derived properties using different instruments including geostationary weather satellites.
• Estimate primary and community production in a Lagrangian frame using velocity fields from a physical ocean model and satellite fields.
• Develop a data-constrained Lagrangian biogeochemical model using times series forecasting and machine learning.

Benefits

• More information on benefits can be found here: USNH Employee Benefits | Human Resources

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees