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Graduate Student Internship: SAI Modeling with AIDE-WACCM

Reflective

San Francisco, CA (San Francisco) permanent

Posted: March 9, 2026

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Quick Summary

Develop and apply novel machine learning models to estimate carbon removal rates for various climate scenarios in the San Francisco, CA region.

Job Description

Sunlight reflection may be the only available option, alongside dramatic emissions reductions, adaptation, and rapid scaling of carbon removal, to rapidly limit many climate impacts over the coming decades. But we don’t know nearly enough about it to make a scientifically-informed decision about potential deployment – and we’re not on a trajectory for rapid, legitimate decision making.

Reflective is a philanthropically-funded initiative to develop the necessary knowledge base and do the requisite technology research and development, urgently and responsibly.

A major bottleneck is that today’s climate models are too slow. A single 100-year run using CESM2-WACCM can take ~35 days, making it impossible to explore the hundreds of parameter combinations necessary for robust policy stress-tests or to resolve the highly parameterized small-scale microphysics.

To solve this, our team is developing AIDE-SAI, a multi-scale surrogate modeling infrastructure. The basis of AIDE-SAI is the surrogate AIDE-WACCM, a machine-learned emulator of large-scale atmospheric dynamics that runs much faster than baseline physics codes in CESM2-WACCM while producing 3-hourly outputs.

INTERNSHIP OVERVIEW

We are seeking a highly motivated Graduate Intern (Ph.D. or Master's level) for a 10-15 week research project. The intern will leverage the newly developed AIDE-WACCM emulator to analyze stratospheric aerosol distributions across diverse injection scenarios.

Because AIDE-WACCM enables rapid scenario generation, the intern will be able to perform robust sensitivity analyses that would be computationally prohibitive with traditional Earth System Models. Working alongside our core science team, the intern can tailor their research to their scientific interests or choose one of several high-priority scientific tracks outlined below.

This is a full-time role based in San Francisco at our office in Embarcadero. Candidates must be US citizens or US residents. Applications will be accepted until March 31, 2026.

POTENTIAL RESEARCH TRACKS

The intern will have the flexibility to choose their own or select one of the following focus areas based on their expertise and research interests:

• Track A: Temporal Injection Strategies & Microphysical Implications

• Objective: Compare continuous aerosol injection against pulsed (daily or weekly) injection strategies.

• Key Metrics: Evaluate radiative forcing (Tg), aerosol lifetime, and effective radius to determine how temporal injection frequency impacts aerosol coagulation and sedimentation.

• Track B: Deep Dive into the Quasi-Biennial Oscillation (QBO)

• Objective: Analyze how the phase of the QBO at the time of injection impacts early-stage aerosol transport.

• Key Metrics: Assess horizontal aerosol spread and vertical dispersion in the critical first few weeks to months following injection across different QBO phases.

• Track C: Stratospheric Heating and Brewer-Dobson Circulation (BDC) Scaling

• Objective: Investigate the dynamical response of the Brewer-Dobson Circulation to stratospheric heating caused by Solar Radiation Modification (SRM). Assess whether the magnitude of BDC alteration (acceleration or structural shifts) scales proportionally with the total stratospheric aerosol burden (Tg) across various injection scenarios, or if critical thresholds/non-linearities exist.

• Key Metrics: Analyze temperature anomalies in the lower stratosphere and changes in BDC strength (e.g., using residual mean vertical velocity, w∗).

• Track D: Model Intercomparison and Lagrangian Transport

• Objective: Conduct a longitudinal comparison of AIDE-WACCM results against the LAGRANTO trajectory model using reanalysis data to validate transport pathways and tracer dispersion.

DESIRED SKILLS AND QUALIFICATIONS

• Currently enrolled in a graduate program (M.S. or Ph.D.) in Atmospheric Science, Climate Physics, Earth System Modeling, or a closely related field.

• Strong programming skills in Python (xarray, numpy, pandas) for large-scale geospatial data analysis.

• Familiarity with stratospheric dynamics (e.g., QBO, BDC) or aerosol microphysics.

• Bonus: Prior experience with WACCM, CESM, or handling outputs from climate model emulators.

COMPENSATION

We are committed to providing competitive compensation and comprehensive benefits to our team. We offer fixed salary levels based on experience and role to minimize biases in compensation and to ensure team members are paid the same for doing the same work. This position is a 10-15 week full-time internship paid $2,000/week.

DIVERSITY

At Reflective, recruiting, hiring, mentoring, and retaining a diverse workforce is critical to our success.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. 

Reflective is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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