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ML and Environment Postdoctoral Fellow
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Position Number: 5732492
Location: Boulder, CO
Position Type: Science - Computer Science

ML and Environment Postdoctoral Fellow

Requisition Number: 59901
Location: Boulder Colorado
Employment Type: Research Faculty
Schedule: Full Time
Posting Close Date:
Date Posted:

Job Summary

The Computer Science Department and the Environmental Data Science Innovation and Inclusion Lab (ESIIL) within CIRES at the University of Colorado Boulder welcome applications for a Post-Doctoral Research Scholar in Machine Learning (ML) and/or Artificial Intelligence (AI) with connection to the field of Environmental Data Science (EDS).

This is an interdisciplinary fellowship aimed at strengthening the connection between core research in ML/AI and EDS. The postdoctoral fellow will have the support and network of the vibrant Computer Science and ESIIL communities at CU Boulder. The postdoctoral fellow will be advised by Professor Esther Rolf (primary mentor) and Professor Claire Monteleoni in the Computer Science Department and an additional mentor in environmental science at ESIIL. The specific mentor(s) in ESIIL will depend on the postdoctoral fellow's research interests.
The University of Colorado Boulder is committed to building a culturally diverse community of faculty, staff, and students dedicated to contributing to an inclusive campus environment. We are an Equal Opportunity employer, including veterans and individuals with disabilities.

Who We Are

Machine Learning for the Environment at CU Boulder CS: This postdoctoral fellow will be advised by Professors Esther Rolf and Claire Monteleoni in the Computer Science Department. Professor Rolf's lab specializes in geospatial and statistical machine learning. Her research group develops computationally efficient models and algorithms tailored to geospatial machine learning with remotely sensed data and analyzes how the representivity of training and pre-training datasets influences the accuracy and equity of machine learning systems across global regions and populations. Professor Monteleoni is the AI/ML Lead for the Environmental Data Science Innovation and Inclusion Lab (ESIIL). Her research group, Climate & Machine Learning Boulder (CLIMB), develops machine learning approaches to confronting climate change at a variety of time-scales.

About ESIIL: The postdoctoral fellow will also have an advisor in the Environmental Data Science Innovation & Inclusion Lab (ESIIL), an NSF-funded data synthesis center led by the University of Colorado Boulder in collaboration with NSF's CyVerse at the University of Arizona and the University of Oslo. ESIIL's mission is to empower an inclusive and diverse community to accelerate open Environmental Data Science. ESIIL is part of the Cooperative Institute for Research in Environmental Sciences (CIRES) at CU Boulder and enables a global community of environmental data scientists to leverage the wealth of environmental data and emerging analytics to develop science-based solutions to solve pressing challenges in environmental sciences. ESIIL's research community generates discoveries and novel approaches through 1) cutting-edge team science, 2) innovative tools and collaborative cyberinfrastructures, 3) data-science education and training, and 4) building inclusive participation and diverse groups. These activities advance the frontier of environmental data science, a rapidly evolving discipline bridging the computational, biological, environmental, and social sciences. ESIIL holds inclusion as a core principle and method for diversifying EDS at a time when society needs all perspectives, and science needs to serve all. ESIIL's vision is grounded in the conviction that innovation and breakthroughs in EDS will be precipitated by a diverse, collaborative, curious, and inclusive research community empowered by open data and infrastructure, cross-sector and community partnerships, team science, and engaged learning.

The "ML for the Environment" Post-Doctoral Research Scholar is expected to produce innovative machine learning research while also representing and encouraging a diverse and interdisciplinary community of ML/AI researchers in the rapidly developing field of EDS.

What Your Key Responsibilities Will Be

Develop and implement a research project that advances machine learning methods, analysis, and/or tools for environmental data science. Examples of relevant projects may include (but are certainly not limited to): developing new machine learning models and methods for efficient, robust, and equitable environmental data science, establishing new benchmark datasets that address gaps in machine learning benchmarks for environmental data science, working with community partners to develop an application-driven machine learning system centered around on-the-ground needs.
Work collaboratively with both members of the Computer Science Department and the ESIIL network. Foster bridges between these communities, for example through collaborative research projects, working group(s), hackathon teams, or trainings for the ESIIL community.
Contribute to the open, reproducible science and education objectives of ESIIL, which include creating and publishing well-documented datasets and codes, FAIR-compliant code workflows, or other outputs that will serve the larger ML and EDS communities.
Effectively share research results with colleagues and the broader science community through peer-reviewed publications, presentations, and other science products.
Interact with a cohort of ESIIL postdocs working on ML/AI applied to various environmental topics. Actively participate in the CS and ESIIL communities and help to promote greater diversity, equity, and inclusion in open environmental data science.

What You Should Know

The anticipated start date is flexible, but is expected to be on or before August 1st, 2025. The selected candidate must have a doctoral degree conferred before the start date of the appointment. This is a one-year position with possibility to renew for a second year dependent on performance.
Location: The Post-Doc will work in person with offices in the Engineering Center and in ESIIL's main office on the CU Boulder campus in Boulder, CO. A hybrid work modality may be a possibility, but will follow current CIRES, Computer Science, and university guidelines and policies. This is not a fully remote position. The in-person cohort experience and engagement with the Computer Science and ESIIL communities is a key aspect of this position.

What We Can Offer

Salary range: $75,000 - $80,000
CIRES and the University of Colorado Boulder offer a robust training curriculum, opportunities for professional development and a Mentorship Program.
Boulder is a vibrant community with access to mountain parks, dog parks, miles of trails, rivers, lakes, cafes, restaurants, boutiques, theaters, museums, and sports venues. Boulder was recently ranked as one of the top places to live in the U.S. by U.S. News.
As an employee at CU Boulder, you will have free access to the regional public transit system, an outstanding network of buses, and light rail systems that service Boulder and connect to Denver, the Denver airport, and surrounding communities.

Benefits

The University of Colorado offers excellent benefits, including medical, dental, retirement, paid time off, tuition benefit and ECO Pass. The University of Colorado Boulder is one of the largest employers in Boulder County and offers an inspiring higher education environment. Learn more about the University of Colorado Boulder.

Be Statements

Be authentic. Be pioneering. Be Boulder.

What We Require

Ph.D. in computer science, or data science field (including but not limited to Computer Science, Data Science, Computer Engineering, Information Science, Math, Economics).

What You Will Need

Knowledge of python programming language and machine learning packages (e.g., Python, PyTorch).
Commitment to Open Science (i.e., available and findable data, reproducible and transferable codes to run on public cyberinfrastructure and open publications) and Open Education.
Effective project management skills (e.g., self-directed, independent).
Collaborative spirit and comfort working in scientifically and culturally diverse and inclusive teams.
Willingness to collaborate and contribute to both the Computer Science and ESIIL research communities (e.g. through working groups, hackathons, and/or summits.)
Willingness to promote diversity, equity, and inclusion in the ESIIL and Computer Science communities.

Special Instructions

To apply, please submit the following materials:

Resume or CV.
A Cover Letter describing your relevant experience, knowledge, and skills, and your professional goals for your postdoc. You may optionally identify up to three potential Environmental Data Science mentors/collaborators within ESIIL that are most relevant to your interests.
A 2-page Research Statement that outlines your planned research project during your postdoc and how it aligns with your past research experience. Please make sure to address how your proposed research will connect core ML/AI research with ESIIL priorities.
A 1-page Statement on Diversity, Equity and Inclusion that outlines how you have contributed to, or would like to contribute to, advancing greater diversity, equity, and inclusion in STEM fields.
List of contact information for three professional references (name, title, professional relationship, email). You do not need to include letters of recommendation with your initial application. If you are selected as a finalist for this role, the search committee will request letters of recommendation at a later time.
(Optional) Transcripts/Proof of PhD: If you are selected as the finalist, your degree will be verified by the CU Boulder Campus Human Resources department using an approved online vendor. If your degree was obtained outside of the United States, please submit an English-translated version (if applicable) as an Optional attachment.

Please apply by December 15, 2024 for full consideration. This posting will remain open until finalists have been identified. Please be prepared to be interviewed if you are selected as one of the finalists.

Note: Application materials will not be accepted via email. For consideration, please apply through CU Boulder Jobs.

In compliance with the Colorado Job Application Fairness Act, in any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

To apply, visit https://jobs.colorado.edu/jobs/JobDetail/ML-and-Environment-Postdoctoral-Fellow/59901