Research Fellow in Digital Manufacturing - Modelling & Simulation

Research Fellow in Digital Manufacturing - Modelling & Simulation London, England

University College London
Full Time London, England 35702 - 37548 GBP ANNUAL Today
Job description

Ref Number
B04-03739
Professional Expertise
Research and Research Support
Department
UCL BEAMS (B04)
Location
London
Working Pattern
Full time
Salary
See advert text
Contract Type
Fixed-term
Working Type
On site (> 80% of working time)
Available For Secondment
No
Closing Date
30-Jun-2023

About us

UCL Department of Chemical Engineering is one of the top research and teaching departments in the UK and has world-class standing. The department offers undergraduate and postgraduate programmes, and has an extensive research portfolio across a wealth of areas, and from molecular scale to complex systems.This position is within the EPSRC project “Development of a machine learning-assisted digital twin platform for real-time optimisation of reaction systems under uncertainty” (https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/X024016/1). This project is a joint collaboration between experts in systems engineering and reactor engineering from UCL and engineers, analytical/process chemists and statisticians from leading chemical and pharmaceutical companies (GSK, BASF, Johnson Matthey) and SMEs (Autichem, Quotient Sciences) to deliver an innovative hardware/software solution tool leveraging automation and physics-informed machine learning technologies to speed up laboratory research and to accelerate process development in chemicals and pharmaceutical manufacturing industries.

About the role

The post-holder will undertake research of significant industrial and academic relevance in the development of a software platform for the automation and optimisation of flow systems in autonomous chemical synthesis. In this EPSRC project the goal is to develop a digital twin platform where physics-informed machine learning (ML) and optimal experimental design algorithms are coupled to enable agile exploration of the chemical process design space, fast identification of optimal reaction conditions and mechanistic understanding of chemical reaction systems using the minimum number of experimental runs.

To achieve these goals, techniques for continuous flow processing, online advanced process analytics, optimal design of experiments, physics-informed ML and advanced data analysis need to be integrated to deliver a fully automated, self-optimizing platform for developing and manufacturing chemicals. The digital twin platform will enable to speed up laboratory research and accelerate process development in the chemicals and pharmaceutical manufacturing industries, facilitating the cost-effective continuous manufacture of chemical products.

This is a fixed-term role for 2 years in the first instance.

Salary is fixed to £39,508 per annum at grade 7 spine point 29. Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Grade 6B (salary £35,702 - £37,548 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD Thesis.

This role meets the eligibility requirements for a skilled worker certificate of sponsorship or a global talent visa under UK Visas and Immigration legislation. Therefore, UCL welcomes applications from international applicants who require a visa.

This appointment is subject to UCL Terms and Conditions of Service for Research and Professional Services Staff. Please visit https://www.ucl.ac.uk/human-resources/conditions-service-research-teaching-and-professional-services-staff for more information.

A job description and person specification can be accessed at the bottom of this page.


About you

The ideal candidate should have completed or near completed a PhD in Chemical Engineering, Computer Science or a related discipline, and have a proven track record of publications in the area of modelling, programming and simulation.The candidate should be able to demonstrate: - Knowledge of model validation techniques- Knowledge of data-driven modelling- Understanding of automation concepts- Understanding of first principles modelling- Knowledge of design of experiments techniques- Proficiency in mathematical modelling, optimisation and/or machine learning Knowledge of Python programming

What we offer

As well as the exciting opportunities this role presents we also offer some great benefits some of which are below:

  • 41 Days holiday (including 27 days annual leave 8 bank holiday and 6 closure days)
  • Defined benefit career average revalued earnings pension scheme (CARE)
  • Cycle to work scheme and season ticket loan
  • On-Site nursery
  • On-site gym
  • Enhanced maternity, paternity and adoption pay
  • Employee assistance programme: Staff Support Service
  • Discounted medical insurance

Visit https://www.ucl.ac.uk/work-at-ucl/rewards-and-benefits to find out more.

Our commitment to Equality, Diversity and Inclusion

As London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong.
We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL’s workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women. You can read more about our commitment to Equality, Diversity and Inclusion here : https://www.ucl.ac.uk/equality-diversity-inclusion/

Our department holds an Athena SWAN Silver award, in recognition of our commitment and demonstrable impact in advancing gender equality.

Research Fellow in Digital Manufacturing - Modelling & Simulation
University College London

www.ucl.ac.uk
London, United Kingdom
Dr Michael Spence
$2 to $5 billion (USD)
10000+ Employees
College / University
Colleges & Universities
Education
1826
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