To make the world a radically better place by applying advanced ML techniques to problems in the weather/climate space
Requirements
- Working experience with Deep Learning Models and data pipelines
- Working experience with Atmospheric/Oceanic numerical models (such as WRF or ROMS)
- Fluent in Python, ML APIs (Tensorflow, Pytorch or JAX)
- Very strong analytical skills
- Ability to gather and analyze large quantities of information, and turn them into insightful business recommendations
- Experience in using distributed computing resources, such as GCP, AWS, Azure or HPC clusters
- Active PhD program in Computer Science, Artificial Intelligence, Atmospheric/Oceanic Science or a related technical field
Responsibilities
- Suggest a number of ways in which ML and other techniques can apply to those challenges
- Prototype solutions
- Work closely with team members to implement solutions
- Lead and participate in cutting-edge research and application in artificial intelligence applied to problems in the climate/weather space
- Develop, implement, and deploy robust, scalable ML/AI solutions for climate/weather applications
- Contribute to code reviews, establish best practices for ML engineering, and optimize code for performance and scalability
- Demonstrate adaptability by rapidly learning and applying AI/ML techniques to new and diverse problem areas as projects evolve
Other
- Active PhD program in Computer Science, Artificial Intelligence, Atmospheric/Oceanic Science or a related technical field
- Excellent communication skills i.e experience writing strategy docs, experience delivering presentations, and a general openness to liaise with senior external partners
- Motivated by making the world a better place through technology, and wanting to be part of a team that makes this happen
- Can do attitude, willing to learn new tools and content to become an effective thought partner with project teams
- An ability to thrive on ambiguity, setting own goals and effectively delivering them in a fast-changing environment
