Postdoctoral Research Associate: Ai & Localized Climate Policy

The Environmental Institute (EI) at the University of Virginia (UVA) is seeking a postdoctoral Research Associate to join its Climate Fellows Postdoc Program. The selected candidate will work with an interdisciplinary team of faculty mentors and researchers to realize the goals of a project aimed atusing advanced AI for simultaneous bias-correction and downscaling of climate model projections for localized policy relevance.
This project explores the capacity of cutting-edge Artificial Intelligence (AI) to simultaneously downscale and bias-correct general circulation climate models (GCMs) climate projections. The general task at hand is to develop AI models that take low-resolution climate maps (produced by GCMs) as input and produce high-resolution counterparts that capture the observed climatic structure (e.g., marginal distribution properties, spatiotemporal dependence, etc) and honor mass conservation. Success of this project will lead to obtaining downscaled and bias-corrected climate projections that are more relevant and actionable at scales that matter for societal decision-making, especially for local governance and community preparedness.
The Postdoctoral Research Associate will work collaboratively with mentors from both the environmental sciences and data science fields across UVA, leveraging their combined expertise to craft new methodologies. The Postdoctoral Research Associate will help pioneer the application of state-of-the-art AI techniques, including knowledge-guided Style Generative Adversarial Networks (StyleGAN) and diffusion models, to simultaneously correct biases and downscale climate projections.
Eligibility and Selection Process:
General Expectations

• Applicants must have received or will receive their doctoral degree by their appointment start date; we prefer candidates who have received their degree within five years prior to the start of the appointment.

• There is no citizenship requirement. UVA will help sponsor visas covering the duration of the postdoc.

• The successful Postdoctoral Research Associate will be appointed for one year with the possibility of second year funding, contingent on the successful completion of a first-year performance review.

• Applicants seeking to be considered for the Postdoctoral Research Associate role for this project will be evaluated on three main criteria:

1. the strength of their research.
2. their ability to collaborate across disciplines; and
3. their commitment to diversifying perspectives and voices in finding equitable solutions for climate adaptation and mitigation.
Project-Specific Competencies
The ideal candidate must demonstrate a diverse set of research skills and methodological approaches, primarily centered around expertise in artificial intelligence, climate science, and data analysis. In addition to a passion for climate science and addressing climate change impacts, the postdoc should have:

• AI and Machine Learning Expertise: Solid background in AI, especially in generative models like GANs, StyleGAN, and diffusion models; adept in neural network design and time series data.
• Data Analysis Proficiency: Skilled in large dataset management and analysis (familiarity with large climatic datasets like CMIP6 data is a plus); statistical expertise in assessing AI model performance.
• Programming Skills: Strong in programming (Python), with experience in TensorFlow or PyTorch; comfortable using high-performance computing and cloud services.
• Methodological Rigor: Capable of designing and validating rigorous experiments; troubleshooting and refining models through feedback.
• Interdisciplinary Collaboration: Experience working in interdisciplinary settings and translating complex AI concepts for diverse audiences.
• Innovation and Adaptability: Creative in problem-solving, capable of pioneering new methods, and thriving in a fast-paced research environment.
• Commitment to Knowledge Transfer: Dedicated to sharing research outcomes, educating others, and mentoring students with strong pedagogic skills.
• Communication Skills (written & oral): Experience publishing research work in scientific journals, giving presentations in scientific conferences etc.

UVA Climate Fellows Postdoc Model:
Once selected, the Postdoctoral Research Associate will join a cohort of other Climate Fellows Program postdocs at UVA and will receive professional training, technical support, and computational infrastructure tailored to their project, for two (2) years. The postdoc will receive direct mentoring from at least two UVA faculty members in different disciplines to help them build cross-disciplinary fluency in support of their own research. They will join a network of faculty members from 30 departments in 12 schools across UVA focused on producing research and providing training that is both great and good at the intersection of climate change and human well-being.
Starting Salary: $65,000/year
Research Funds: $5,000/year
We partner with the Office of Graduate and Postdoctoral Affairs, UVA's Career Center, and staff across the university to provide career development and extracurricular opportunities to student and postdoctoral faculty.
About the Institute:
The UVA Environmental Institute is the hub of interdisciplinary environmental research at the university. We provide seed funding, research experiences, and training to faculty, postdoctoral fellows, and students from the university's 12 schools. With a focus on impactful research, the Institute and its collaborators are committed to our mission to support interdisciplinary research and training that is both great and good at the intersection of climate change and human well-being, while ensuring that the full spectrum of human attributes, perspectives, identities, backgrounds, and disciplines is represented and making an explicit effort to diversify voices in finding equitable solutions for climate adaptation and mitigation.
The University of Virginia is rated as one of the top three public universities in the nation and in the top 30 among all universities, public and private. Charlottesville is frequently cited as one of the best cities in which to live and work. The University of Virginia is an equal opportunity and affirmative action employer.
To Apply:
External Applicants: Apply online, and search for 'R0055867.' Complete an application online and attach the following:

• CV/Resumé
• Cover Letter, describing your research interest and how it aligns with the project.
• Personal Statement (highly encouraged, but not required): use this statement to reflect on your academic and research trajectory; you may include a description of how your experiences relating to race, ethnicity, gender, or any other kind of identity marker have shaped your ability to contribute to the University of Virginia.
• Contact information for three (3) references (name, email, telephone, and address).

Internal UVA Applicants: Please apply through your Workday Home page, search "Find Jobs."
Application Timeline:

• Application Opens: December 18, 2023
• Early application reviews begin on January 20, 2023

For questions about the position, please contact Henry Boachi, Program Manager, at henryb@virginia.edu.
For questions regarding the application process, please contact Jessica Speth, Academic Recruiter, at js9rk@virginia.edu.
The University of Virginia, including the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician's Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experiences. We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.