The science behind Cervest

Addressing some of the most complex and interesting challenges in Earth Science AI and climate.

 

Our world-leading scientists and researchers have published 60+ peer-reviewed scientific papers in journals ranging from Nature Climate Change and PNAS to Journal of the Royal Statistical Society.

Our key areas of research include: deep learning, non-parametric Bayesian, hybrid modelling, transfer learning, spatio-temporal modelling and multi-task learning. 

Current explorations (by research residents) include ethics of climate AI, de-noising clouds though deep learning (GANS), and optimising weather data for dynamic ML modelling.

Our research partners and collaborators

Research Residencies

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, as well as social sciences. A typical project lasts 3-6 months (with flexibility on this). 

 

Past and present Research Residents

Agnes Schim van der Loeff 

Research Resident

Ruiao Hu

Research Resident

James Walsh

Research Resident

Mike Zotov

Research Resident

Research Residents: FAQs

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 you’ll find 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 can I expect from the programme?
Our research programme is very similar to an 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. Our ideal candidate has either a degree or equivalent experience in STEM fields. We strongly encourage candidates with a non-traditional backgrounds and experiences. 

Ruiao Hu
Research Resident

A computer scientist by trade and a mathematician at heart, Ruiao graduated from Imperial College London with an MEng degree in Joint Mathematics and Computer Science.

With industry experience in data engineering gained with world-leading finance firms, Ruiao has joined Cervest for the summer to construct data pipelines for a number of our upcoming projects.

Just as he joined Cervest, Ruiao achieved a first class MEng degree with the Governor’s Prize and Corporate Partnership Programme award for his final year project. After his time at Cervest he will pursue a PhD in stochastic geometric mechanics under the supervision of Prof Darryl Holm at Imperial College London.

James Walsh
Research Resident

James is a Statistical Scientist with a bachelor’s degree in the subject awarded from the Statistics department at the University of Warwick.

James joins Cervest as part of his work with the Warwick Manufacturing Group and The Alan Turing Institute where he is a Research Assistant developing Physically Informed Hybrid models.

He will be spending his time at Cervest applying this expertise to simulating individual crop growth and constructing bulk processing technologies for modelling organic carbon content for soil quality monitoring. He has also worked in the risk team of financial consultants at Albourne Partners building simulations.

Mike Zotov
Research Resident

Mike has recently graduated with a first class honours degree in Mathematics from the University of Warwick.

Having studied Machine Learning as part of his degree, he has joined Cervest for the summer to work on deep generative models for de-noising remote-sensing data.

After his time at Cervest he will continue to pursue his passion for Machine Learning with a Master’s degree at Imperial College London.

Agnes Schim van der Loeff
Research Resident

Agnes recently graduated with a first class honours BA in Arabic and Development Studies from SOAS University of London. Alongside her studies she has also worked as Environment Officer in the SOAS students’ union. Passionate about environmental justice, she plans to pursue a master’s degree in political ecology.

Agnes has joined Cervest to research the ethical implications of AI in relation to climate change and food security, and thus help ensure Cervest’s pioneering technology adheres to the highest ethical standards. With her social science background she is interested in the social, economic and political dimensions of climate change and will therefore also conduct policy-related research to inform Cervest’s engagement with policy makers.