The Power and Energy Division of the Department of Electrical and Electronic Engineering at The University of Manchester, Manchester, UK is looking for a Postdoctoral Research Associate to work on the development and implementation of a probabilistic, artificial neural networks based methodology for modelling demand-side flexibility in distribution networks. The methodology will serve to represent demand flexibility coming from a large number of residential and small and medium-size commercial end-users. The resulting model will be applicable to the flexibility procurer, quantifying the amount of available capacity in the presence of uncertainties. Such a comprehensive flexibility model can inform demand response (DR) programmes at the distribution level, facilitating more confident planning of the DR outcome, and scheduling demand manipulation in an optimal way. This research will contribute to more flexible operation of the distributing network by assessing the time varying capacity available from flexible loads, in response to flexible services currently procured by the DNOs.
You will collaborate with industrial stakeholders (DNOs and Aggregators) in the UK to ensure industrial relevance and applicability of the developed methodology. This post will require regular meetings with industrial collaborators in the UK, preparation of high quality journal and conference publications, presenting research at leading international conferences, as well as the ability to interact effectively with other researchers and engineers.
As this role involves research at a postgraduate level, applicants who are not an EEA national or a national of an exempt country and who will require sponsorship under the Skilled Worker route of the UK Visas and Immigration’s (UKVI) Points Based System in order to take up the role, will be required to apply for an Academic Technology Approval Scheme (ATAS) Certificate and will need to obtain this prior to making any official visa application UKVI)
As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
Our University is positive about flexible working – you can find out more here
Blended working arrangements may be considered
Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.
Enquiries about the vacancy, shortlisting and interviews:
Name: Dr Jelena Ponocko
Email: jelena.ponocko@manchester.ac.uk
General enquiries:
Email: People.Recruitment@manchester.ac.uk
Technical support:
https://jobseekersupport.jobtrain.co.uk/support/home
This vacancy will close for applications at midnight on the closing date.
Please see the link below for the Further Particulars document which contains the person specification criteria.
