Description

The Department of Atmospheric and Oceanic Sciences (ATOC) at the University of Colorado Boulder invites applications for a full-time, tenure-track Assistant Professor in Boundary-Layer and Coupled Earth System Processes with Physics-Informed Artificial Intelligence (AI).

This position addresses critical research and instructional frontiers at the intersection of boundary-layer meteorology, coupled Earth-System processes, and scientifically grounded machine learning. The atmospheric boundary layer governs crucial multiscale exchanges between the atmosphere, land, ocean, ice, ecosystems, and human systems, directly influencing extreme weather, air quality, wildfire behavior, water resources, and renewable energy. Such processes also represent a primary source of uncertainty in Earth system prediction models and constitute a defining challenge for computational methods.

The successful candidate will develop an internationally recognized, externally funded research program focused on advancing both explainable AI methodology and Earth system science through physics-informed, physics-constrained, or hybrid process–AI modeling. Candidates will be expected to teach and mentor students at both the undergraduate and graduate levels, contribute to core ATOC curricula and develop courses in boundary-layer physics, environmental data science, and physics-informed machine learning for weather and climate. 

CU is an Equal Opportunity Employer and complies with all applicable federal, state, and local laws governing nondiscrimination in employment. We are committed to creating a workplace where all individuals are treated with respect and dignity, and we encourage individuals from all backgrounds to apply, including protected veterans and individuals with disabilities.

Who We Are

ATOC is a world leader in investigations of climate science and weather phenomena, from the depths of the ocean to the outer reaches of the atmosphere. Our highly recognized research and education programs include theory, modeling, and measurements from the ground, balloons, aircraft, and satellites. ATOC faculty and graduate students address fundamental questions of societal relevance in the areas of climate processes and weather dynamics, aerosol and cloud physics, atmospheric chemistry and transport, radiative transfer, fluid dynamics, and oceanography. ATOC undergraduates delve into a breadth of applied science topics, acquiring the quantitative skills necessary for today's high-tech careers. 

What Your Key Responsibilities Will Be

Intellectual Vision & Research: Establish a vibrant research group that leads developments of physics-informed AI, hybrid modeling frameworks, or data-driven methods that bridge physical laws with scientific discovery. Areas of interest include, but are not limited to:

   AI-enabled parameterizations of turbulence, surface exchange, and unresolved boundary-layer physics.
   Process discovery and data fusion integrating heterogeneous in-situ observations, remote sensing, and high-resolution numerical simulations.
   Hybrid and reduced-order modeling of coupled atmosphere–surface, ocean, sea ice, and terrestrial interactions.
   Explainable, generative, and physically consistent machine learning methods for investigating weather regimes, climate extremes, and ensemble prediction.

Teaching & Mentorship: Teach undergraduate and graduate courses in atmospheric and computational Earth system sciences, supervise graduate student research, and provide hands-on research opportunities for undergraduates that emphasizes physical reasoning, responsible AI, and scientific computing.

Service & Collaborative Leadership: Engage with campus-wide computational initiatives and leverage Boulder’s premier scientific ecosystem—including high-performance computing resources (Alpine and Blanca clusters), regional observational infrastructure (Marshall Field Site), and partnerships with local federal laboratories (NOAA, NSF NCAR, NREL). 

What You Should Know

This is a full-time, tenure track position. 

What We Can Offer

   The annual salary range for this full-time position is 110,000 - $118,000.
   A startup package, moving allowance, and recruitment incentive may be available to the successful candidate per department guidelines. 

At the University of Colorado Boulder, we are committed to supporting the holistic health and well-being of our employees. Our comprehensive benefits package includes medical, dental, and retirement plans; generous paid time off; tuition assistance for you and your dependents; and an ECO Pass for local transit. As one of Boulder County’s largest employers, CU Boulder offers an inspiring academic community and access to world-class outdoor recreation. In fact, CU Boulder has been named one of Forbes' America's Best Large Employers, ranking #4 among large employers in Colorado and #28 among universities nationwide. 

Special Instructions

Application Link: Assistant Professor (Tenure Track)

Full consideration will be given to applications received by December 1st, 2026. Review of applications will begin on this date and continue until the position is filled. Applications will no longer be accepted after June 1st, 2027. 

Informal inquiries can be made to the search committee chair, Aneesh Subramanian, at aneeshcs@colorado.edu.

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

Requirements

What We Require

Ph.D. in Atmospheric Science, Oceanography, Earth System Science, Applied Mathematics, Computer Science, Engineering, or a related discipline at the time of appointment.
Demonstrated potential to establish an impactful, externally funded research program at the nexus of boundary-layer processes and physics-informed AI.
A strong commitment to effective teaching, student mentorship, and developing inclusive learning environments in computational and Earth system sciences. 

What You Will Need

Deep domain knowledge in boundary-layer physics, atmospheric dynamics, meteorology, and/or coupled Earth system processes (e.g., atmosphere–ocean, land–atmosphere, or cryosphere interactions).
Expertise in machine learning and computational methods, such as physics-informed neural networks (PINNs), hybrid modeling, model emulation, generative modeling, and/or scientific data assimilation.
Ability to formulate independent, innovative research proposals and secure external funding from agencies such as NSF, NOAA, DOE, NASA, DOD, and/or private ventures.
Commitment to pedagogical excellence, inclusive teaching, and mentoring undergraduate and graduate students from diverse disciplinary backgrounds.
Strong written and oral communication skills that foster interdisciplinary collaboration across atmospheric science, applied mathematics, computer science, and engineering.