Postdoctoral Positions

Postdoc position in global terrestrial carbon and water cycle and machine learning

The department of Earth and Environmental Engineering of Columbia University in the City of New York invites applications for a Postdoctoral Position in the field of terrestrial carbon and water cycles, using machine learning, under the supervision of Prof. Pierre Gentine https://gentinelab.eee.columbia.edu. The position is part of the USMILE European Research Council Synergy grant: a large international project for improving climate projections and observations. The project will involve frequent collaborations with other groups working on other aspects of the Earth system and on the development of new machine learning tools. The applicant should have a background in terrestrial water and carbon cycles, and ideally advanced experience in machine learning. Candidates should have recently completed their Ph.D. or should expect to complete their degree requirements by January 2022.

Our group strives to improve and ensure work-life balance for their employees.

Please send CV and inquiries to: Pierre Gentine pg2328@columbia.edu 

Postdoc position in stable boundary layer and machine learning

The department of Earth and Environmental Engineering and Earth Environmental Sciences of Columbia University in the City of New York invite application for a Postdoctoral Position in the field of atmospheric boundary layer under the supervision of Prof. Pierre Gentine. The position is part of M²LInES https://m2lines.github.io/: a large international project for improving climate predictions and especially surface temperature biases using machine learning in Earth system models. The project will involve frequent collaborations with other groups working on other aspects of the Earth system (ocean, sea ice or convection), on the development of new machine learning tools as well as on strategies to improve surface temperature predictions. The applicants should have a background in atmospheric or oceanic physics as well as exposure to machine learning and/or statistics and Earth system modeling. Candidates should have recently completed their Ph.D. or should expect to complete their degree requirements by September 2021.

Candidates from underrepresented groups are especially welcome to apply. Our group also strives to improve and ensure work-life balance for their employees.

Please send CV and inquiries to: Pierre Gentine pg2328@columbia.edu 

Data Scientist

We are developing a set of tools for water risk estimation and its financial implications for water utilities, water users and for financial risk hedging. We seek individuals with machine learning and statistics backgrounds with an interest in climate risk, financial instruments and water systems. Prior work has developed multi-century reconstructions and simulation tools for streamflow across the continental USA, and estimates of water use by sector, as well as risk metrics. The candidate will help extend these methods to develop predictions of risk across the USA at seasonal to decadal time scales, and link it to concepts such as Value at Risk or Conditional Value at Risk in different contexts.

Please send your information to ula2@columbia.edu with PDAPPLICANT1 in the subject line.

Water Systems Analyst

Many areas of the USA have been experiencing deterioration in water and wastewater services, with accompanying ecological and human health concerns. Aging infrastructure as well as poor choices for the architecture of the infrastructure are often a factor. We are trying to develop the first comprehensive identification of the water and wastewater infrastructure condition and needs across the USA so that efforts to remedy the situation can be properly directed. Minority and economically disadvantaged populations are of particular interest. In addition to the need identification, we want to develop tools that allow an exploration of the financial and technical applicability of decentralized water and wastewater treatment and reuse systems as a function of scale. We see this as the direction for the future. The candidate of interest would have skills in network optimization, smart systems, sensors and control, and be adept in spatio-temporal data analytics.

Please send your information to ula2@columbia.edu with PDAPPLICANT2 in the subject line.

Urban Disaster Response and Resilience for Smart Cities

Networked smartphones and sensors provide an unprecedented ability to monitor and dynamically respond to emerging conditions during disasters. In the context of New York City, we are exploring how one can plan and execute strategies for responding to a disaster in a highly spatially specific way given the ability to acquire a variety of data in and out of buildings, and with evolving conditions related to hurricane or nor-easter induced flooding with impacts on multi-modal mobility systems. The candidate would have analytical capabilities and interests in this topic, including but not limited to network analysis, natural language processing, machine learning and remote sensing applications.

Please send your information to ula2@columbia.edu with PDAPPLICANT3 in the subject line.

Send a separate email for each position if you have more than one interest.

If you do not match the skills indicated for the position, please do not apply.