Data analytics methods are increasingly being applied to understanding materials discovery, processing parameters in manufacturing, and materials performance.
We are looking for a data scientist with an interest in manufacturing and engineering who can utilise techniques to classify data, and basic machine learning algorithms and tools to model manufacturing processes and materials discovery to support parameter optimization and decision making to reduce, or even avoid, waste and ineffective interim steps.
The goal of this project is to utilise a range of data analytics techniques and methods to study the design, manufacture and validation of alloys, porous structures and their performance in applications such as bioengineering, automotive, heat transfer, electrochemistry and food technologies.
The post is fixed term for 12 months and can be held remotely or on-campus. Full time or a lower FTE (i.e. Part-time) would be considered and is to be discussed with the candidates at interview.
For more information refer to the Job Description and Person Specification.
For informal enquiries please contact SMT admin wssmt-admin@lboro.ac.uk
Our Benefits
• Generous annual leave allowance up to 44 days (inclusive of Bank Holidays & University closure days)
• Competitive pension schemes
• A range of childcare support initiatives and benefits including childcare vouchers; on-site university nursery (with salary sacrifice scheme); and holiday play schemes.
• We offer a range of family friendly, inclusive employment policies.
• BUPA Cash Plan (100 scheme)
• Employee Assistance Programme
• Season ticket loan scheme
• On campus parking with charging points for electric vehicles
• Fantastic range of sports facilities and preferential membership packages available
• Fantastic CPD and inclusive resources for development
Application closing date: 15 October 2024
Application URL: