Job description

Wolfson School of Mechanical Electrical and Manufacturing Engineering

This is a fixed term post for 12 months and can be held FULL or PART-TIME

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 ( Part-time) would be considered and is to be discussed with the candidates at interview.

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