We are a team of impatient optimists who want to make a lasting, positive and sustainable impact across the planet – by doing science! We believe the benefits of scientific thinking should be accessible, affordable and used to empower those managing nature’s resources – growers, buyers and policymakers – to adapt to rising climate volatility.
As such, we are seeking a diverse set of candidates eager to ask questions that have not been asked before in the fields of earth sciences, AI and statistical sciences. A typical project lasts 3-6 months (with flexibility on this) and could consist of tasks such as:
- reading and synthesising academic papers;
- data engineering and feature extraction;
- implementation of a reproducible data processing pipeline;
- exploratory data analysis;
- implementation of benchmark models;
- implementation of ML algorithms / inference for statistical models;
- validation of models using simulated data;
- systematic and reproducible comparison of models using real data;
- presentation of research results;
- write-up of research results and submission to an academic conference;
- submitting pull requests for code reviews, to ensure project is maintainable and to share knowledge within the team.
We are looking for candidates who have:
- strong coding skills;
- strong quantitative knowledge in statistics/mathematics/physics/econometrics or earth science;
- some research experience and ability to take ownership of a research project;
- curiosity, creative problem-solving skills and an interest in climate-related issues.
Research Residency FAQ:
- Where can I see some examples of Research Residence projects?
You can learn more about the research projects completed by our residents on our blog. Here is an example of work completed by Agnes on systemic impacts of combination of AI & Earth sciences at scale. Or Mike’s work on remote sensing denoising using deep latent variable generative models.
- What to expect from the program?
Our research program is very similar to academic Masters or PhD but with a spin of an open and welcoming start-up culture. You will be reading papers, leading an independent research project, and of course you will receive the best possible mentoring experience from our science and engineering team. Closer to the end of your residency you will be expected to share your work in the best possible medium, that being a blog post or an academic publication at a conference paper or a workshop.
- Who should apply?
Most important for us, is that you are mission driven, hungry to learn, and have a strong interest in earth sciences, machine learning, and the implications of this combinations on policy and societies. Ideal candidate has either a degree or equivalent experience in STEM fields. We strongly encourage candidates with a non-traditional backgrounds and experiences.
- How do I apply?
Please send us your CV and a brief cover letter on email@example.com. Since we expect a high number of applicants, after sending us your CV you will hear back from us with a selection of exercises to complete.