Research Associate in Power System Dynamics and Machine Learning Applications

Job title:

Research Associate in Power System Dynamics and Machine Learning Applications

Company

University of Manchester

Job description

The Power & Energy Division at the University of Manchester comprises 22 academic staff and a team of over 120 research staff and students. The Division’s research activities range from the design of power electronic circuits to the analysis and control of complete energy conversion systems and utility networks. Applications of particular interest include the active management of power networks including smart grids, Flexible AC Transmission Systems (FACTS), integration of HVDC into power networks, renewable power generation (especially wind), as well as more-electric aircraft and ships. As such the Division offers one of the strongest research environments within any UK university for undertaking electrical power research.With around 70 academic staff, the Department of Electrical and Electronic Engineering is one of the largest of its type in the country and has about 850 undergraduates, 350 taught postgraduates, and 260 research students.Overall Purpose of the JobThis role is part of a 4+3 years research programme funded by a UK Research and Innovation Future Leaders Fellowship (https://gtr.ukri.org/projects?ref=MR%2FY00390X%2F1), specifically liked to the +3 years renewal, led by Dr. Panagiotis Papadopoulos, around the area of “Addressing the complex dynamic behaviour of future power systems”.The Fellowship is aiming at investigating and developing necessary models, novel methods and tools to address the increasing uncertainty and complexity introduced in power system dynamic behaviour by the connection of new technologies (e.g. renewable generation, electric vehicles, storage devices, HVDC interconnectors, etc).The post is fixed term for 12 months and the Grade appointment will depend on qualifications (e.g. holding a PhD or not) and skills.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 hereBlended working arrangements may be consideredPlease 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 Panagiotis PapadopoulosEmail: panagiotis.papadopoulos@manchester.ac.ukGeneral enquiries:Email: People.Recruitment@manchester.ac.ukTechnical support:Jobtrain: 0161 850 2004 https://jobseekersupport.jobtrain.co.uk/support/homeThis 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.

Expected salary

Location

Manchester

Job date

Mon, 30 Sep 2024 22:20:55 GMT

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