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Job advertisement Research scientists at Earth Rover Program: sensor engineering, machine learning, seismology related to soil.

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European Geosciences Union

Research scientists at Earth Rover Program: sensor engineering, machine learning, seismology related to soil.

Research scientists at Earth Rover Program: sensor engineering, machine learning, seismology related to soil.

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Earth Rover Program

Earth Rover Program (ERP) is a not-for-profit organization which started in November 2023, headquartered in the UK. Making novel use of cheap and dispatchable technologies, its purpose is to improve our knowledge of the soil, both enhancing scientific understanding and enabling farmers to raise fertility and crop production while reducing environmental impacts. This is a major initiative, supported by Bezos Earth Fund over the first 2.5 years, during which we will benchmark and image soils below-ground, improving our understanding of their properties on sites around the world. The initial research phase will enable us to refine the methodology before pursuing its further development and deployment. Our approach has the potential to help address one of humanity’s most urgent challenges: feeding the world within environmental limits.

ERP has been co-founded by Simon Jeffery, Reader in Soil Ecology at Harper Adams University; George Monbiot, author of Regenesis and Honorary Fellow at Wolfson College, Oxford; Tarje Nissen-Meyer, Professor of Geophysics at the University of Oxford / now Professor in Environmental Intelligence at the University of Exeter; and Katie Bradford, Operations Specialist working with climate organizations. The team seeks to expand the initiative with a range of further funders to support innovations in agriculture, food systems, soil science, and monitoring as a key solution to addressing the climate crisis.


Remote, preferably in or near UK to travel to meetups (other arrangements globally can be discussed). Engineering, machine learning and seismology positions can be seconded through the University of Exeter, UK; soil science at Harper-Adams University, UK., United Kingdom of Great Britain – England, Scotland, Wales


Relevant divisions
Geosciences Instrumentation and Data Systems (GI)
Seismology (SM)
Soil System Sciences (SSS)



ERP operates mostly as a remote organisation, but the positions can be linked to/seconded via University of Exeter, UK, according to UK postdoc salaries. Salaries are generally competitive with the corresponding job market, depending on location.

Required education

Application deadline
25 April 2024

12 April 2024

Job description

Working as part of Earth Rover Program’s core team, we are recruiting research scientist positions (in particular sensor engineering and machine learning) to support designing and executing the scientific proof-of-concept of ERP, at competitive salaries with flexible work arrangements (regarding location, full-time/part-time) for highly motivated, independent, creative and engaged individuals with a strong cross-cutting collaborative work ethic.

A prerequisite is evidence of independent research (PhD, publications) in at least one of:

  • engineering (micro-/electric/structural engineering, e.g. on MEMS, piezoelectric sensors);
  • machine learning, data science (data ingestion/fusion, augmentation, inference, classification);
  • seismology (modelling, theory, inverse methods, sensor technology, experiments);
  • soil science (soil analyses, spatial statistics, GIS, remote sensing).

Place of work: ERP operates as a mostly remote team, with quarterly in-person meetups around the UK. Soil science positions may be located at Harper-Adams University, all other positions can be remote or associated with the University of Exeter. We are open to applications from candidates based anywhere, though flexibility may be required in core working hours to accommodate multiple time zones within the team. Some roles may include travel to fieldwork locations in the UK and/or elsewhere around the world.

Start date/duration: We expect to onboard new roles between now and summer 2024, in line with the development of the project. This phase of the funded project finishes in spring 2026, but we anticipate further expansion and longer-term funding

Outcomes: The involvement in this research-intensive environment is expected to lead to high-profile publications, high visibility, global collaborations across disciplines, with equal footing in fundamental science and clear solution-oriented impact for public benefit.

Support: We seek independent researchers in the core team to collaborate closely, under the continuous guidance of science leads Dr Jeffery and Dr Nissen-Meyer. Support funds exist for work-related travel and equipment. We strive to build a vigorous, diverse and inclusive environment with flat hierarchies and strong support on health and wellbeing matters. Remote work requires proactive communication skills, and the work environment will feel like somewhere between academic, non-profit and industrial research, with distinct timelines for producing outcome.


Engineering: ERP’s mission relies on effective data acquisition with vibrational sensors. ERP’s diverse portfolio of existing sensors, and further acquisitions, require profound benchmarking for the context of soil monitoring in terms of instrument sensitivities, noise, robustness, potential scalability (cost, autonomy, ease of use, data flow and storage). A core task will be to develop a plan, based on the above findings, for optimal sensing of natural environments, including potentially bespoke instrumentation with onboard computing, for instance leveraging raspberry pi or similar hardware and software approaches. This will include field tests, data analysis in close cooperation with ERP’s geophysics team, and collaboration with software engineers on onboard computing and phone apps.

Machine learning: ERP’s central component will be built upon machine learning, databases, data analysis and inference algorithms. This includes a variety of data science tasks: Generating effective data ingestion from a diverse, heterogeneous and increasing flow of large datasets, data fusion to allow for scientific inference across multimodal datasets, building modern, effective machine-learning algorithms for classification, Bayesian/causal inference, uncertainty quantification, and effective interrogation of a vast database. This first post will devise the basic framework of the infrastructure in close cooperation with the geophysics and soil science teams, and will lead to a larger group focussed on building a virtual ERP environment, with a digital soil twin at its core.

Geophysics: Complementing ongoing seismology efforts, a geophysics post could focus on modelling seismic wavefields using numerical and machine-learning algorithms, developing inversion frameworks. An alternative post may focus on building an experimental lab for elastic, mechanical, physical properties of soil materials. This is a long-term goal requiring careful planning; experience with laboratory infrastructures is thus required.

Soil science: This post will entail contributing to the successful execution and completion of experimental work to provide the soil analysis ground truthing elements of the seismology. It will include assisting in the running of high frequency seismology field experiments and the set up of controlled laboratory experiments and combine elements of digital soil mapping to further assist the development of 3D maps of soil characteristics and structure.

How to apply

Please use the form linked below to apply. Applications sent by email will not be considered.

We welcome applications from anywhere and anyone with relevant skills and backgrounds who feels they can positively contribute to and grow with the project.

Please submit your application until April 25, 2024 23:59 GMT via this form, which will require uploading the following documents:

  • research statement including past experience and relevance for our posts (2 pages)
  • CV, including email addresses for 3 referees familiar with your past research (2 pages)
  • list of publications, highlighting three most relevant papers with links to full paper (1 page)
  • brief statement on logistics (500 words): where you would like to be based, when you could start, and whether full-time or part-time (this will not affect the judgement on your suitability for the technical aspects of the position, but a start date by summer/autumn 2024 is desirable).

Text exceeding the above-stated lengths will not be considered.

Timeline: Upon receipt of applications, we will request letters of recommendation for shortlisted candidates, and perform virtual interviews in early May. We anticipate extending offers of employment by mid May for a start date as early as June 2024, and ideally no later than September 2024.

Questions? Can be submitted to the team using the form above, prior to job application.