Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.
Our base salary range is $167,030 - $260,570, and in addition we have generous bonus plans to provide a competitive compensation package.
Who You Are:

We seek one or more Research Scientists for a new three-year project to develop an AI-powered physics-informed hybrid climate model trained on historical data that is capable of multidecadal forecasts that are more accurate than the current state of the art. We're looking for someone with experience in AI and earth science who is excited to push the frontier in climate model development.

This position is supported by a grant with a current period of performance ending September 22, 2029. Continuation of the position beyond that date depends on renewal, extension, or identification of additional funding. Ai2 will make reasonable efforts to notify the employee if funding for the position is expected to end.

Your Next Challenge:

Physically-based climate models discretize equations representing individual time-evolving processes like clouds, rain, wind, land and sea-ice, and ocean currents on a computational grid. Some processes (e.g. clouds) are less reliably encoded than others (e.g. winds). Hence such climate models have biases in representing present-day climate and produce an undesirably large range of projections of future climate change for a given human-caused change in CO2 or other climate forcings. Current AI-based climate models reduce present-day climate bias, but don't generalize well to future climate change.

We are starting a 3-year project funded by google.org to develop an open source 'AI-first' climate model that can demonstrably project future climates more accurately than current physically-based climate models when trained on historical observations by judicious design of the AI to incorporate physical principles that reliably apply in any climate, seen or unseen. The model should be lightweight and easy for an ML-savvy climate scientist to train and deploy. Our starting point is the Google Research NeuralGCM model, a hybrid ML model that uses a conventional discretization of winds encoded in JAX and learns a column-local representation of all other atmospheric and land processes from historical data. Compared to other AI climate models, NeuralGCM uses ML in a conceptually simpler way and shows somewhat better future-climate generalization skill. It is an open-weight model but its training pipeline and documentation need to be adapted for a broader user community.

You will join a small team to develop the desired NeuralGCM+ model and foster its uptake by the climate modeling community. This includes coupling it to an ML-based ocean model and designing approaches to demonstrably improve its skill in unseen climates. This position has a three year term; there is potential for longer-term funding if the NeuralGCM+ project demonstrates exceptional progress.

You'll get to work on:

• Designing, implementing and testing a strategy for coupling NeuralGCM with the chosen ocean model. Note that NeuralGCM is written in JAX and implemented on TPUs.
• Designing, implementing and testing a strategy for decomposing physical parameterizations and constraints into parts encoded based on physical equations vs. parts that can be learned (even for unseen climates) from historical observations.
• Presenting results at major relevant AI and climate modeling conferences and in peer-reviewed publications.
• Open-source code development as part of a tightly connected team, including daily meetings, code review, design documents and interaction with external collaborators.
• Mentoring postdocs and interns.

What You'll Need:

• You must have substantial experience building and deploying a relevant ML application in a practical or academic research setting and be fluent in Python and collaborative coding practices.
• You must have a Ph. D. in computer or computational science, applied mathematics/statistics, or atmospheric science or a related geophysical science, with at least one accepted conference paper or peer-reviewed first-authored publication making extensive use of ML.
• Demonstrated excellent communications skills.

It's A Bonus If You:

• Have formal training and/or practical experience with physically-based atmospheric, oceanic, or related model development.
• Have previously held a professional or post-doctoral position using your machine learning skills.
• Have experience writing machine learning code in JAX.
• Formal graduate-level ML coursework.

Physical Demands and Work Environment:

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

• Must be able to remain in a stationary position for long periods of time.
• The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations.
• The ability to observe details at close range.
• Can work under deadlines.

Benefits:

• Team members and their families are covered by medical, dental, vision, and an employee assistance program.
• Team members are able to enroll in our health savings account plan, our healthcare reimbursement arrangement plan, and our health care and dependent care flexible spending account plans.
• Team members are able to enroll in our company's 401k plan.
• Team members will receive $125 per month to assist with commuting or internet expenses and will also receive $200 per month for fitness and wellbeing expenses.
• Team members will also receive up to ten sick days per year, up to seven personal days per year, up to 20 vacation days per year and twelve paid holidays throughout the calendar year.
• Team members will be able to receive annual bonuses and can participate in the long-term incentive plan.

Note: This job description in no way states or implies that these are the only duties to be performed by the team members(s) of this position. Team members will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the team member(s) will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities. This document does not create an employment contract, implied or otherwise, other than an at will relationship.