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Advanced Research Fellow: Machine Learning, Climate Solutions Catalyst - Undaunted

Imperial College London

Location: London, Hybrid
Salary: £63,485 to £75,184 plus benefits
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 13th February 2024
Closes: 6th March 2024
Job Ref: NAT01645
 

South Kensington and White City Campus - Hybrid

The Grantham Institute for Climate Change

The Grantham Institute – Climate Change and the Environment, was established at Imperial College London in 2007 to act as a central hub to pull together the different work taking place across the university that can help tackle climate change and environmental challenges. The innovation dimension of the Grantham Institute’s work is run under the banner Undaunted.

Undaunted’s mission is to nurture a climate innovation ecosystem that enables the creation of scalable innovative solutions to the climate challenge at pace. To achieve this mission, Undaunted is building a pipeline of routes into climate entrepreneurship, incubating innovators through our Greenhouse accelerator programme, delivering an ecosystem that empowers impact and creating a landscape where climate innovation can flourish.

We are now launching an exciting new experimental activity at the very start of the climate innovation pipeline: the Climate Solutions Catalyst. The objective of the programme is to test the hypothesis that the UK university sector has already made discoveries and inventions that can help tackle climate change, if only they can be found and supported properly. Working collaboratively with as many other UK universities as possible, and a full range of stakeholders, this two-year trial programme will try and unearth neglected climate solutions from the full breadth and depth of the UK research community, and then test potential support offers for these solutions and the researchers and innovators that discovered them.

Duties and responsibilities

The machine learning research fellow will have a critical role in designing and delivering the machine learning dimension of this project and integrating it into the work of others in the team who will be forming relationships across the UK and delivering human search dimensions. We would expect the postholder to maintain good working relationships with a range of key actors and be focussed on using their research for practical outcomes.

As the only technical machine learning specialist in the team, we will expect the post holder to be able to explain their approaches in plain English to others and integrate user needs and other priorities effectively into their approaches.

You will be an active member of the Undaunted team, working with other members of the team to deliver on our wider mission to drive forward climate innovation in the UK and beyond.

Essential requirements

Our ideal candidate will have excellent technical skills with an understanding of how to apply these skills in a practical setting to deliver outcomes. You will have interest in applying your skills to the climate change problem space where innovations are needed, coupled with the natural curiosity required to support the delivery of this programme.

The successful candidate will have a combination of strong analytical and communication skills.

Further information

Please note this role will be based at both South Kensington and White City Campus

Should you require any further details about the role please email: Gosia Gayer: g.gayer@imperial.ac.uk

This is a hybrid role. Staff working in roles that are suitable for hybrid working will normally be expected to work 60% of their time onsite. The opportunity for hybrid working will be discussed at interview.

More information is available on the following web page: Work Location Framework | Administration and support services | Imperial College London

Closing: 6 March 2024

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