Research Fellow in Data-driven Dynamical Models of Earth\'s Core
Research Fellow in Data-driven Dynamical Models of Earth\'s Core

Research Fellow in Data-driven Dynamical Models of Earth\'s Core

Leeds Full-Time 36000 - 60000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Join us to develop data-driven models of Earth's core dynamics and predict space-weather hazards.
  • Company: Be part of the University of Leeds, a top UK research institution with a vibrant academic community.
  • Benefits: Enjoy 42 days of holiday, a generous pension scheme, and access to a state-of-the-art gym.
  • Why this job: Work on groundbreaking research with global impact while collaborating with leading experts and institutions.
  • Qualifications: PhD (or nearing completion) in geophysics, physics, or applied mathematics with strong computational skills required.
  • Other info: Flexible working arrangements and travel opportunities for conferences included.

The predicted salary is between 36000 - 60000 £ per year.

This role will be based on the university campus, with scope for it to be undertaken in a hybrid manner. We are also open to discussing flexible working arrangements.

Are you an ambitious researcher looking for your next challenge? Do you have a background in machine learning or fluid dynamics and an interest in applying your skills to understand the dynamics of Earth's fluid core and space-weather hazard? Do you want to further your career in one of the UK's leading research intensive Universities?

We are seeking a Research Fellow to fulfil a key role in our project to:

  • Produce new data-driven models of the magnetohydrodynamics of Earth's core
  • Better understand and predict the south Atlantic Anomaly (SAA), a region of weak magnetic field intensity in the south Atlantic in which spacecraft are exposed to high energy radiation.

The SAA is the primary focus of the recent Macau satellite mission MSS-1 whose observations will be integral to the project. You will be based in the deep Earth research group within the School of Earth and Environment at the University of Leeds and work closely with Professors Phil Livermore and Chris Davies (SEE), collaborating with Drs William Brown and Ciaran Beggan at the British Geological Survey (BGS). You will also work with a variety of external project partners: Macau Institute of Space Technology and Application, British Antarctic Survey, and the Technical University of Denmark; and a project stakeholder group including the Met Office, the European Space Agency, RiskAware and RAL Space.

There will be travel opportunities to work in-person with this network of collaborators, as well as for presenting the research at national and international conferences. This work is part of the NERC-funded project “A new paradigm for the geodynamo: data-driven models of core dynamics that explain and predict Earth's magnetic shield” between the University of Leeds and BGS.

You will begin by mapping the SAA using both geomagnetic and high-energy particle data as measured by the MSS-1 mission. You will also (if required) learn how to use physics-informed neural networks (PINNs) and how they can be applied to the fluid dynamics of Earth's core where the global magnetic field is generated. Using a numerical geodynamo simulation as a benchmark, you will undertake a thorough investigation of both local and global PINN reconstructions of the modelled core using sparse synthetic magnetic field observations.

Next, you will develop a suite of PINN models, simultaneously constrained by the equations of magnetohydrodynamics and global magnetic satellite data from 1999-present including data from MSS-1. You will use these models to infer dynamics and structures hidden from observation, such as the internal flow, magnetic field, temperature, and stratification profile. Finally, you will use these models to investigate the underlying dynamics of the SAA, and predict its future and associated space-weather hazard over the next 20 years.

Throughout the project, you will help coordinate 6-monthly meetings with the project partners and stakeholders, ensuring two-way communication about project findings but also areas to focus on to maximise impact.

You will have a PhD (or close to completion) in geophysics, physics, applied mathematics or similar highly numerical discipline with a strong background in computational modelling or scientific machine learning. You will also have the ability to conduct independent research and a developing track record of publications in international journals. In addition, you will have excellent communication, planning, and team working skills.

Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first-time applicants might need to qualify for salary concessions. For more information please visit: www.gov.uk/skilled-worker-visa.

For research and academic posts, we will consider eligibility under the Global Talent visa. For more information please visit: https://www.gov.uk/global-talent.

What we offer in return:

  • 26 days holiday plus approx. 16 Bank Holidays/days that the University is closed by custom (including Christmas) – that’s 42 days a year!
  • Generous pension scheme plus life assurance – the University contributes 14.5% of salary.
  • Health and Wellbeing: Discounted staff membership options at The Edge, our state-of-the-art Campus gym, with a pool, sauna, climbing wall, cycle circuit, and sports halls.
  • Personal Development: Access to courses run by our Organisational Development & Professional Learning team.
  • Access to on-site childcare, shopping discounts and travel schemes are also available.
  • And much more!

To explore the post further or for any queries you may have, please contact:

Research Fellow in Data-driven Dynamical Models of Earth\'s Core employer: University of Leeds

The University of Leeds is an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration among researchers. With generous benefits including 42 days of annual leave, a robust pension scheme, and access to state-of-the-art facilities, employees are supported in both their professional and personal development. The opportunity to engage with leading experts and contribute to impactful research projects makes this role particularly rewarding for ambitious individuals seeking to advance their careers in a prestigious academic environment.
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Contact Detail:

University of Leeds Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Research Fellow in Data-driven Dynamical Models of Earth\'s Core

Tip Number 1

Network with professionals in the field of geophysics and machine learning. Attend relevant conferences or workshops where you can meet researchers and potential collaborators, especially those associated with the University of Leeds or the British Geological Survey.

Tip Number 2

Familiarise yourself with the latest research on magnetohydrodynamics and the South Atlantic Anomaly. Being well-versed in current studies will not only enhance your understanding but also allow you to engage in meaningful discussions during interviews.

Tip Number 3

Demonstrate your ability to work collaboratively by highlighting any previous team projects or interdisciplinary work. This role involves coordination with various partners, so showcasing your teamwork skills will be crucial.

Tip Number 4

Prepare to discuss how you would apply physics-informed neural networks (PINNs) in your research. Having a clear plan or examples of how you could implement these models will show your initiative and readiness for the role.

We think you need these skills to ace Research Fellow in Data-driven Dynamical Models of Earth\'s Core

Machine Learning
Fluid Dynamics
Computational Modelling
Scientific Machine Learning
Data Analysis
Numerical Simulation
Magnetohydrodynamics
Physics-Informed Neural Networks (PINNs)
Geophysics
Applied Mathematics
Research Coordination
Communication Skills
Team Collaboration
Publication in International Journals
Project Management

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, fluid dynamics, and computational modelling. Emphasise any research projects or publications that align with the role's focus on Earth's core dynamics.

Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the position and the specific project. Discuss how your background and skills make you a perfect fit for the research goals, particularly in relation to the south Atlantic Anomaly and data-driven models.

Highlight Collaborative Experience: Since this role involves working with various partners, mention any previous collaborative projects you've been part of. Showcase your ability to communicate effectively and work within a team, as these skills are crucial for this position.

Showcase Your Research Skills: Detail your research methodology and any experience with physics-informed neural networks (PINNs) or similar techniques. Provide examples of how you've applied these skills in past projects, especially if they relate to geophysics or magnetohydrodynamics.

How to prepare for a job interview at University of Leeds

Showcase Your Research Background

Be prepared to discuss your previous research experiences, especially those related to geophysics, machine learning, or fluid dynamics. Highlight any publications or projects that demonstrate your ability to conduct independent research and your familiarity with computational modelling.

Understand the Project's Focus

Familiarise yourself with the specifics of the project, particularly the south Atlantic Anomaly and its implications. Being able to articulate how your skills can contribute to understanding and predicting this phenomenon will impress the interviewers.

Demonstrate Team Collaboration Skills

Since the role involves working closely with various partners and stakeholders, be ready to provide examples of how you've successfully collaborated in a team setting. Discuss your communication strategies and how you ensure effective coordination in group projects.

Prepare Questions for the Interviewers

Think of insightful questions to ask about the project, the team, and the university's research environment. This shows your genuine interest in the position and helps you assess if it's the right fit for you.

Research Fellow in Data-driven Dynamical Models of Earth\'s Core
University of Leeds
U
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