Young Investigator, Climate Modeling
About The Position
This is 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. The position has a three-year term. The Ai2 Climate Modeling team is an international pioneer in using machine learning (ML) methodologies to improve on current physics-based climate models. Our fast, accurate autoregressive open-source emulator, ACE, stably reproduces the climate and weather extremes of an existing climate model or a reanalysis. We have coupled ACE to a ML ocean model, trained it to realistically account for changing CO2 concentrations, and downscaled (super-resolved) ACE outputs from their 100 km native scale to to km-scale detail. Our tight-knit team of scientists and software engineers works closely with leading physics-based climate modeling centers to obtain unique training and testing data and get expert feedback on our progress. We collaborate with other leading research groups doing related AI work.
Requirements
- Substantial experience building and deploying a relevant ML application in a practical or academic research setting.
- Fluent in Python and collaborative coding practices.
- Ph. D. in computer or computational science, applied mathematics/statistics, or atmospheric science or a related geophysical science.
- At least one accepted conference paper or peer-reviewed first-authored publication making extensive use of ML.
- Demonstrated excellent communications skills.
Nice To Haves
- Formal training and/or practical experience with physically-based atmospheric, oceanic, or related model development.
- Experience writing machine learning code in JAX.
- Formal graduate-level ML coursework.
Responsibilities
- Select, design and evaluate NeuralGCM+ training and testing cases, using both historical data and customized physics-based climate model outputs.
- Conceiving and implementing NeuralGCM+ model improvements that increase its generalizability to unseen climates and improve the simulated coupling between earth system components such as the atmosphere, ocean, land, and sea ice, in collaboration with other team members.
- 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 interns as appropriate.
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Employee assistance program
- Health savings account plan
- Healthcare reimbursement arrangement plan
- Health care and dependent care flexible spending account plans
- 401k plan
- $125 per month to assist with commuting or internet expenses
- $200 per month for fitness and wellbeing expenses
- Up to ten sick days per year
- Up to seven personal days per year
- Up to 20 vacation days per year
- Twelve paid holidays throughout the calendar year
- Annual bonuses
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
