Process Control & Optimisation Engineer

Vacancy: Process Control & Optimisation Engineer Location: UK Flexible Our Efficient Natural Resources Sector is currently running a transformation programme to support the execution of the sector strategy using digital tools and technology. We are currently recruiting for a Process Control & Optimisation Engineer to develop and provide data-driven solutions to improve process understanding and implement for the control and performance improvement of JM's process technologies. Key aspects of this capability are managing the associated data workflow (collaboration with JMIT) as well as pre-processing of the data (reconciliation, cleaning), feature selection and building digital models using multivariate statistics and machine learning methods. The successful candidate will be responsible for growing our internal capability to apply data-driven solutions to existing and new business problems in order to help us achieve our sector strategy. Key responsibilities: Undertake specific projects by data processing, analysis and statistical / machine learning modelling to provide insight for operations improvement and to deliver options for data-driven model-based control Analyse complex measurement data and relate these to critical process stream attributes using statistical or ML techniques Analyse plant operating data using statistical and machine learning techniques; build relevant physical models, and reduced versions thereof Develop data driven or hybrid models as a basis for process and product control and optimization (including predictive maintenance) and validate models through pilot scale work or using operating plant data Contribute to the design and requirements specification for data toolset to improve statistical approaches within JM Work collaboratively with the Core Engineering and Smart Manufacturing team at Chilton to deliver digital solutions to the sectors for process management, operations improvements and process control Work with the Product Owner(s) and Product Manager in each area to understand requirements, develop hypotheses and then test and implement measurement and control innovations Work with other business stakeholders and JMIT to 'productionise' models so that they can be built into service offerings for JM Track actions, remove blockers and coordinate planning activities for new initiatives and experiments Track and report on success metrics and KPIs for experiments Produce communications events for sector staff on new digital capabilities Are you the ideal candidate? You will have: Degree in Chemical Engineering (preferred), Chemistry, Electrical Engineering, Mathematics or other related discipline Relevant postgraduate experience in process measurement, control engineering, process data analytics or the application machine learning / artificial intelligence methods Strong capability in relevant mathematical methods such as: signal processing, multi-variate statistics, physical modelling, machine learning (artificial intelligence) Experience in catalyst or materials research and/or JM-related manufacturing processes Experience in processing large data sets and coding for data manipulation Experience in modelling, preferably use of multi-variate statistics and/or machine learning Data manipulation, processing and coding skills PhD / EngD related to process measurement, control engineering or process data analytics is desirable How to apply: If you have the necessary skills and experience to join our team, please apply online. Closing date for applications: 27 September 2021 Johnson Matthey Plc is an equal opportunities employer and positively encourages applications from suitably qualified and eligible candidates regardless of sex, race, disability, age, sexual orientation, marriage or civil partnership, pregnancy or maternity, religion or belief. This job was originally posted as

Similar searches: Permanent, Full Time, Pharmaceutical & Science, Royston