Senior Research Fellow In Machine Learning, Urban Systems Lab

The Urban Systems Lab (USL) at The New School invites applicants for an appointment as a Senior Research Fellow in Machine Learning.
The Urban Systems Lab is an interdisciplinary research, design and practice space at The New School that provides knowledge and analysis for developing more equitable, resilient, and sustainable cities. The Lab's work advances cutting edge science, data visualization, and computation to develop systemic solutions to social and environmental challenges driving inequity and injustice in urban areas. We bring together designers, urban ecologists, scientists, researchers and policymakers with the goal to improve the lives of those most vulnerable, and to enhance decision making and science communication from local to global scales. To learn more visit: http://urbansystemslab.com
The Schools of Public Engagement comprise the School of Media Studies, the School of Undergraduate Studies, the Milano School of Policy, Management, and Environment, the Creative Writing Program, and the Julien J. Studley Graduate Programs in International Affairs, as well as several programs, research centers and institutes; the Urban Systems Lab is among them. You can find more information on The Schools of Public Engagement here: https://www.newschool.edu/public-engagement/
The New School, a private university in New York City's Greenwich Village, serves undergraduate and graduate students across a range of fields with a commitment to bringing practices in design and social research to studying issues of our time and challenging students to become engaged citizens dedicated to solving problems and contributing to the public good.
The New School is strongly committed to diversity and inclusion in the workplace and particularly seeks applications from members of underrepresented groups, as well as candidates who share this commitment.
POSITION OVERVIEW
We are seeking an outstanding scholar with expertise in Machine Learning, urban data science, and spatial modeling to co-lead the development of our AI driven climate risk software. The Fellow will work with diverse local and global databases to model and analyze urban climate risks to help build our Google.org funded ClimateIQ model, an integrated AI driven climate risk modeling environment and data visualization tool that provides near term and future flood risk data in urban areas. The Fellow will work closely with the Lab's Director and Assistant Director to advance Machine Learning capabilities for the modeling environment, and work with a team of climate modelers to validate data and processes. This is a stellar opportunity to work with a diverse global team of climate scientists, researchers and modelers across the world including with partners at Google, Climasens, Stockholm Resilience Center, Virginia Climate Center and more leveraging cutting edge technologies and data science to improve planning and urban climate adaptation across the world. This is a 3 year fixed term, Full Time benefit eligible position with the possibility of renewal or extension contingent on funding. This position will report directly to the Director of the Urban Systems Lab.
RESPONSIBILITIES

• Work with a diverse team of modelers and data scientists to develop a Machine Learning model that uses advanced AI algorithms, e.g., CNNs, to create an integrated modeling environment for the ClimateIQ tool.
• Co-lead Machine Learning model development, including back-end coding, cloud computation integration, and supporting data science.
• Participate in all hands meetings with research team members and stakeholders.
• Produce technical reports and presentations to provide updates on milestones and deliverables.
• Contribute to active research projects with partners at the George Mason University, Climasens, Stockholm Resilience Centre, Princeton Environment Institute, and The Beijer Institute of Ecological Economics at the Royal Swedish Academy of Sciences within its program "Governance, Technology and Complexity" and its international initiative "AI, People and Planet".

MINIMUM QUALIFICATIONS
The selection among eligible candidates will be based on:

• A Master's or Doctorate in a field that uses computer science to solve real-world problems, such as geospatial modeling, urban modeling, or data mining.
• Demonstrated extensive experience in Machine Learning, including deep learning algorithms, CNN or related ML methods, and cloud-based GPU computing.
• Experience working with Google Earth Engine, Python, R, and associated libraries.
• Experience working in software engineering team or code development team to deliver research products on timelines.
• Geospatial analytical skills as they apply to urban system dynamics.
• Strong statistical analytical skills including spatial statistics.
• Familiarity with urban resilience, climate change, complex systems, and scenario development literature.
• Strong organization, communication, and writing skills for coordinating research with international colleagues and research dissemination.
• Demonstrated academic and other outputs in the form of scientific publications and/or public repositories such as GitHub.
• Willingness and ability to work as part of a multi- and transdisciplinary team with varying backgrounds and expertise.
• Commitment to The New School's EISJ principles.
• Ability to adhere to the university's COVID-19 policy.

PREFERRED QUALIFICATIONS
The following skills are preferred, but not required:

• Experience and publications on spatial analysis of urban flooding, vulnerability and risk.
• Climate scenario modeling including potential work with CMIP6 global scenarios.
• Dynamic integrated modeling is a plus as is experience working with multi-hazards or cascading hazards.
• Expertise in the use of Google Earth Engine and Google Colab for geospatial data analysis and visualization.
• Expertise in extract, transform, and load (ETL) processes for data migration and integration.
• Familiarity with geoprocessing workflows and geospatial analysis design.
• Comfort with Machine Learning in quantitative modeling environments.
• Experience in the fields of: Climate Change Adaptation, Resilience, and/or Disaster Risk Reduction.

WORK MODE
On-campus Position: The USL Research Fellow is expected to work on-campus due to the nature of the work.
Salary Range:
$65,000 - $70,000 depending on experience
TO APPLY
Review of applications will be on a rolling basis and open until filled.
Interested candidates should submit:

• a cover letter describing the applicant's research, scholarship and work experience relevant to this position
• a curriculum vitae
• names and contact information of three references

We look forward to receiving your application!