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Research Associate in Information Theoretic Tools for Manufacturing

University of Sheffield - Department of Automatic Control and Systems Engineering

Location: Sheffield
Salary: £31,302 to £39,609 per annum (Grade 7).
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 18th February 2019
Closes: 21st March 2019
Job Ref: UOS021695

Contract Type: This post is fixed-term until 30 September 2020 to start as soon as possible.

Are you interested in working for a world top 100 University? We have an exciting opportunity in the University of Sheffield’s Department of Automatic Control and Systems Engineering for someone with a passion for information theory and its applications to intelligent manufacturing systems. This research associate position is funded by the EPSRC awarded project Circular 4.0, which focuses on the development of data-driven tools to optimise the selection of Circular Economy strategies for products and the timings of interventions in the product lifecycle. This particular position will target using information-theoretic tools to provide quantitative measures of the data streams generated within modern manufacturing processes.  

You should hold a PhD (or be close to completion) in any relevant area of engineering, computer science or mathematics, such as information theory, communication theory, data science, probability theory, high-dimensional statistics, stochastic processes, etc. The post will contribute to Sheffield’s reputation as the leading centre of digitisation and informatics research for manufacturing. 

While you will have an opportunity to build on your own research experience and strength to contribute to the research project, you will also contribute to Sheffield’s reputations as the leading centre of digitisation and informatics research for manufacturing. 

Automatic Control and Systems Engineering (ACSE) is one of the largest departments devoted to the subject in Europe. We are a world-leading research department, as evidenced by the results of the 2014 Research Excellence Framework (REF2014) exercise - out of 62 UK institutions specialising in multi-disciplinary and inter-disciplinary engineering, the Department was ranked first for quality of research publications and third for overall research quality. The principal investigator for this post is Professor Ashutosh Tiwari, who is Airbus / RAEng Research Chair in Digitisation for Manufacturing at the University of Sheffield. The Line Manager for this post is Dr Iñaki Esnaola, Senior Lecturer in the Department of Automatic Control and Systems Engineering at The University of Sheffield. 

We’re one of the best not-for-profit organisations to work for in the UK. The University’s Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and professional development. 

We build teams of people from different heritages and lifestyles whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience. 

Follow @sheffielduni and @ShefUniJobs on Twitter for more information about what makes the University of Sheffield a remarkable place to work. 

Closing date 21 March 2019.

This post is fixed-term until 30 September 2020 to start as soon as possible.

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