The Quadracci Sustainable Engineering Lab (QSEL) works on solutions that could advance well-being and economic growth through both access to energy, water and infrastructure as well as creating and enabling income generating opportunities in emerging economies. In recent years, we have increasingly been asked to help identify opportunities and binding constraints at granular scale using national-scale data of populations, land-use, economic activity and infrastructure to support the ability of private sector and governments to leverage opportunity and address constraints. The incumbent will be contributing to 'Using Data to Catalyze Energy Investments', a Columbia World Project.
The primary job responsibilities of this position are to: 1) implement deep learning models for identifying cropland, seasonal changes in vegetation, distinguish between horticulture and cereal crops and possible use of irrigation. Inform on value of variety of label data sets and time series radar imagery as well as daytime high-resolution imagery. 2) develop associated code base for multi-sensor image processing and analysis, 3) test, validate and scale-up predictions, 4) document methodology and write publications, and 5) work closely with collaborators and practitioners.
Ph.D. in computer science, data science, environmental science, engineering, landscape ecology or a closely related field;
Extensive experience in machine learning for image analysis;
Strong programming skills;
Excellent written communication skills demonstrated by prior publications; and
A track record that demonstrates the ability to work well with interdisciplinary research teams.
Experience with processing multi-spectral satellite imagery; computer vision.
Strong programming skills in Python, Pytorch, KERAS, TensorFlow; and
Experience with cloud-computing tools for geospatial computing (e.g. Google Earth Engine) will be considered advantageous.
Columbia University is an Equal Opportunity Employer / Disability / Veteran
Pay Transparency Disclosure
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.
Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the university to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.