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 residency@cervest.earth. 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.

Ernesta Baniulyte 
Product Designer

Ernesta has been a full-stack product designer for more than five years. She has valuable experience in the B2B, B2C and B2B2C worlds, and while working at both agencies and product/service companies, she has learned to develop UX research infrastructures to support strategy.

At Cervest, Ernesta contributes to all stages of the product development process – from initial ideation to the exacting detail of UI design – finding new ways to visualise data, and ensure our product is intuitive and user friendly.

Ernesta’s decision to join Cervest was inspired by her desire to make the world a safer, better and more aware place.

Ramani Lachyan 
Junior Research Scientist

Ramani joined Cervest after obtaining her Master’s in Physics from ETH, Zurich. She brings with her valuable experience gained through working on model building and data simulation pertaining to neutrino physics.

Ramani has joined Cervest as a Junior Research Scientist and will be working on creating algorithms that allow for the extraction of physical observables from data from a range of sources.


Lukas Scholtes 
Statistical Scientist

Lukas completed his maths BSc at ETH Zurich, followed by an MSc in statistics at Imperial College. He wrote his MSc thesis in collaboration with Cervest, on the modelling of North American wheat yields via Bayesian parametric and non-parametric methods.

Following an internship in the NGO sector in Bangladesh and a stint in the world of fintech, Lukas comes to Cervest, excited to apply himself to the challenges that are arising as a consequence of unsustainable land-use policies and climate change.

Aidan Coyne
Junior Researcher

Aidan is currently pursuing a Bachelor of Arts and Sciences in Science and Engineering at University College London with a focus on computer science and data informatics.

At Cervest, Aidan is working on researching and assimilating a database of articles categorising the reasons for extreme decreases in crop yields across Europe. The information will be used to help predict the impact of weather events on crop yield and contribute to  Cervest’s ability to bring clarity to decision making around climatic and extreme events.

While studying, she also volunteers with environmental conservation groups and youth engagement programmes.

Jasmine Thompson
Engineering Resident

Jasmine’s background is primarily in Python programming with a focus on data analysis and visualisation.

Since graduating, she has worked on data insights for a London-based dating app startup, helping the company understand the user base and guide new growth. She is now excited to use her skills to help Cervest deliver playback data and useful data analysis and is passionate about the potential of data science, machine learning and visualisation tools.

While studying at Westcliff High School for Girls she was involved in a variety of projects including GUI design for BAE Systems and data collection for a surveillance vehicle project sponsored by Leonardo S.p.A. She was also the Data Analyst for a long-running Southend Youth Council project that advocated for students having better mental health services in school.

Stoyan Binev
Junior Software Engineer

Stoyan is a BSc student at King’s College London with two years’ experience in software engineering.

With experience working for Amazon and Google as a software engineer, as well as for a fintech start-up, Stoyan was inspired to join Cervest’s by its planet-wide scale and the opportunity to make a positive impact in the world.

He is currently finishing his degree and dissertation while also specialising in data processing at Cervest.

Agnes Schim van der Loeff
Policy Researcher

Agnes joined Cervest after completing her BA in Arabic and Development Studies from SOAS University of London. She is interested in the intersection of the social, economic and political dimensions of climate change and passionate about climate justice. During her studies she was also engaged in environmental activism, including as environment officer in the SOAS students’ union.

Agnes started at Cervest as a research resident exploring the ethical implications of AI in relation to climate change, which resulted in a paper selected for an oral presentation at the NeurIPS 2019 workshop on AI for social good. Building on this, she is developing an ethical framework for Cervest. As policy researcher she now does research on the regulatory context of Cervest’s work and on emerging policies relating to climate change. 

Kate Chkhaidze
Machine Learning Scientist

Kate joined Cervest after completing her PhD study at the Institute of Cancer Research, University of London. Her Project was on statistical and computational modelling of cancer evolution. Her educational background is in pure mathematics (BSc – Tbilisi State University) and statistics (MSc – Imperial College London). Before deciding to study for a PhD, she worked as a junior analyst/developer at the Bank of Georgia and in parallel was giving lectures in Statistics to undergraduate students in Tbilisi for almost two years.

At Cervest, she will be working as a Machine Learning Scientist on crop classification problems. She loves the mission and goal of the company and is very excited to be a part of the process of achieving it.