Research Assistant in Critical Mineral Supply Chains and Machine Learning

Location: Central Cambridge 

We have an exciting opportunity for a Research Assistant in Critical Mineral Supply Chains and Machine Learning in the Cambridge Critical Materials Lab (www.ccml.org.uk), as part of the Climate Compatible Growth (CCG), funded by the UK's Foreign, Commonwealth and Development Office (FCDO). This aims to support sustainable energy and transport systems to meet development priorities in the Global South. This post is for a Machine Learning Engineer to research and model critical mineral supply chains and to effectively communicate the research results to a wide audience.

The post holder will be located in Cambridge, UK. This is a full-time position and offered on an initial fixed- term contract basis for six months, starting as soon as possible.

The key responsibilities and duties are:

• Research into critical mineral supply chains
• Modelling of supply chain risks
• Scientific Writing and Reporting
• Planning and organising
• Project collaboration

The skills, qualifications and experience required to perform the role are:

• Applicants must have a Master's degree level (1st or high 2.1 equiv.) in engineering, from a top University
• Knowledge and experience in: 

1. 1. Investigating critical mineral value chains
   2. Network systems analysis
   3. Machine learning techniques
   4. Using Python to create code
   5. Using Github to collaborate and organise code 

• Exceptional writing skills across different contexts (i.e. research, media and policy) and interpersonal collaborative skills

Salary Range: Research Assistant: GBP 33,002 - GBP 35,608

Fixed-term: The funds for this post are available for 6 months in the first instance.

To apply online for this vacancy and to view further information about the role, please click 'Apply' above.

Please ensure that you upload your Curriculum Vitae (CV), a covering letter and publication list in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please submit your application by midnight on the closing date.

If you have any questions about this vacancy or the application process, please contact: Prof. Jonathan Cullen (jmc99@cam.ac.uk) for queries of a technical nature related to the role, or Dr Luc Le Lay (ll221@cam.ac.uk) for queries related to the application process.

Please quote reference NM49250 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

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