Research Associate in Palaeointensity Determination from Chemical Remanent Magnetisation (ChemPI)

Research Associate in Palaeointensity Determination from Chemical Remanent Magnetisation (ChemPI)

Job number ENG04048 Faculties Faculty of Engineering Departments Department of Earth Science & Engineering Salary or Salary range £50,733 - £59,484 per annum Location/campus South Kensington Campus - Hybrid Contract type work pattern Full time - Fixed term Posting End Date 3 Nov 2026

About the role

This Postdoctoral Research Associate position is part of a NERC-funded project to develop ChemPI, the first absolute palaeointensity protocol for chemical remanent magnetisation (CRM). The aim of this project is to recover reliable ancient magnetic field strengths from rocks whose remanence is chemical rather than thermal in origin, and to apply the new protocol to some of the most consequential open questions in early Earth science.

All current methods for determining absolute palaeointensities assume that a rock's remanent magnetisation formed on cooling, a thermoremanent magnetisation. Many rocks, especially from the Precambrian, have instead been remagnetised by chemical processes during metamorphism or metasomatism, producing a chemical remanent magnetisation (CRM) whose intensity existing methods can underestimate by more than half. This matters for some of the biggest open questions in Earth and planetary science, including when the Earth's inner core nucleated, whether early Earth had a magnetosphere capable of protecting a habitable atmosphere, and how magnetic fields shaped the protoplanetary disc. You will combine new micromagnetic models, machine-learning inversion of magnetic hysteresis data and laboratory-synthesised CRMs to build and ground-truth ChemPI, then apply it to 3.7-billion-year-old rocks from Isua, Greenland, to test whether the early Archean geomagnetic field was stronger than currently thought.

This position at Imperial will lead the experimental development and application of ChemPI under the guidance of Adrian Muxworthy and Dominik Weiss, whilst the numerical and micromagnetic modelling aspects of the project are undertaken at Edinburgh, and the application to Archean samples is led from Oxford.

What you would be doing

Working with the NERC project PI Adrian Muxworthy (Imperial), Co-Is Dominik Weiss (Imperial), Wyn Williams (Edinburgh) and Claire Nichols (Oxford), you will develop and ground-truth the ChemPI palaeointensity protocol. This will involve synthesising samples in the laboratory and collecting natural samples, making room-temperature magnetisation measurements, and developing micromagnetic models to predict CRM behaviour. Working with Edinburgh, the project will extend a machine-learning inversion algorithm and micromagnetic CRM database to interacting particle assemblages, and contribute to a user-friendly, open-access ChemPI web app. In the final phase you will apply ChemPI, with Oxford, to re-examine palaeointensity estimates from 3.7-billion-year-old samples from Isua, Greenland.

What we are looking for

• You will have experience of palaeomagnetic or rock-magnetic measurement techniques, such as demagnetisation, hysteresis or FORC measurements.
• You will ideally have experience of laboratory synthesis of materials.
• You will ideally have some experience of micromagnetic modelling or machine-learning approaches to magnetic data.
• You will have published or submitted first-author peer-reviewed scientific papers.
• You will be comfortable working independently and collaboratively across three institutions, with regular visits to Edinburgh and Oxford.
• You will have a PhD in Earth Science, Physics, Materials Science, Chemistry or a closely related discipline.

What we can offer you

• A chance to develop the first absolute palaeointensity method for chemical remanent magnetisation, with applications ranging from early Earth habitability to planetary science.
• The opportunity to work across three leading UK palaeomagnetic and micromagnetic modelling groups (Imperial, Edinburgh and Oxford), combining experiment, machine learning and software development.
• The opportunity to continue your career at a world-leading institution

Further information

This is a full-time, fixed term position for up to 30 months.

Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.

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