Postdoctoral Research Associate I (UPDATED) (MULTIPLE POSITIONS)

University of Arizona - Tucson, AZ

Part-time,Full-time - Entry Level

Tucson, AZ

Educational Services

About the position

The University of Arizona is seeking a Postdoctoral Research Associate I to join the Social Pixel lab, focusing on mapping floods using machine learning and satellite imagery. This role aims to understand inequity in urban flood adaptation and to build capacity for environmental justice organizations. The position is funded through an NSF Career Award and NASA grants, specifically targeting the project "Addressing flood justice and equity impacts of adaptation and urban expansion with satellite observations." The postdoc will lead the development of two critical databases: the US Floodplain Mitigation Infrastructure Database, utilizing FEMA GIS data, and the US Flood Extents in Revised Floodplains Database, which will incorporate satellite data including Planetscope data and public sensors. The successful candidate will enhance existing models with innovative methods to create a historic US flood database, enabling end-users to generate flood maps tailored to their communities. The role involves deploying machine learning models of high accuracy, collaborating with existing research assistants and postdocs to refine deep learning models of inundation, and improving on current Convolutional Neural Network (CNN) models across six sensors using advanced techniques such as transformers. The Social Pixel lab emphasizes applications for social and environmental justice, providing opportunities to engage with stakeholders outside academia, including government, business, and non-profit organizations. This position offers flexibility in the full-time equivalent (FTE) and includes outstanding benefits such as health, dental, vision, and life insurance, paid vacation, sick leave, and holidays, as well as tuition reduction for employees and their qualified family members. The University of Arizona is recognized for its innovative work-life programs, making it an attractive workplace for researchers.

Responsibilities

• Collaborate with PI and students to deploy deep learning models to identify and monitor water in satellite imagery time series using sensors such as MODIS, VIIRS, Sentinel-1, and Planetscope.
• Build a database of flood mitigation infrastructure in the US.
• Build a history of flooding in the US at spatial high resolution.
• Write articles for publication (co-authored and first-authored).
• Support organization of meetings, collaboration, and lead NASA funded projects related to flood mapping in Bangladesh and near real-time flood mapping using VIIRS.
• Present results at AGU, AAG, or other relevant conferences.
• Support grant proposal writing efforts and developing proof of concepts (including opportunities to lead one's own).
• Collaborate with partners at NASA to implement flood water detection models in satellite imagery.

Requirements

• PhD in Geography, Environmental Sciences, Computer Science, or related field upon hire.
• Experience in Remote Sensing and GIS.
• Experience in Machine Learning preferably using Python.
• At least one first authored publication in a referred journal.

Nice-to-haves

• PhD in Geography or Environmental Science.
• Experience programming in Google Earth Engine.
• Experience with data fusion (radar, optical imagery, of various spatial and temporal resolutions).
• Experience working on urban adaptation.
• Experience working with end users, especially environmental justice organizations or communities.
• Experience working with hydrological data (such as stage/discharge measurements, surface water measurements).
• Experience in training deep learning models, such as convolutional neural networks, using Pytorch or Fastai.
• Experience in data engineering - curating and maintaining labeled training datasets for deep learning.
• Experience with transformers, LSTMs, and other deep learning modalities.

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• Life insurance
• Paid vacation
• Sick leave
• Paid holidays
• Tuition reduction for employees and qualified family members
• Access to UA recreation and cultural activities