Research Assistant/Research Fellow - 15655 (4389) | Brunel University London Skip to Content

Research Assistant/Research Fellow - 15655

The College of Engineering, Design and Physical Sciences at Brunel University London has been awarded a grant by InnovateUK as academic partner in a consortium for Shoreside Power from Optimised Hydrogen Lifecycle (SPOHL).

College / Directorate
College of Engineering, Design & Physical Sciences
Department
Department of Electronic & Electrical Engineering
Full Time / Part Time
Full Time
Posted Date
22/04/2024
Closing Date
20/05/2024
Ref No
4389

Position Title: Research Assistant/Research Fellow - 15655 

Department/College: Department of Electronic and Electrical Engineering

College of Engineering, Design and Physical Sciences 

Location: Brunel University London, Uxbridge Campus 

Salary: 

Research Assistant: Grade R1 from £35,490 to £37,488 per annum inclusive of London Weighting with potential to progress to £38,532 per annum inclusive of London Weighting through sustained exceptional contribution. (Pro-rata for Part-time) 

Research Fellow: Grade R1 from £39,607 to £44,240 per annum inclusive of London Weighting with potential to progress to £46,771 per annum inclusive of London Weighting through sustained exceptional contribution. (Pro-rata for Part-time) 

Hours: Full Time 

Contract Type: Fixed Term Contract until 31 March 2025

 

Brunel University London was established in 1966 and is a leading multidisciplinary research-intensive technology university delivering economic, social and cultural benefits. For more information please visit: https://www.brunel.ac.uk/about/our-history/home 

The College of Engineering, Design and Physical Sciences at Brunel University London has been awarded a grant by InnovateUK as academic partner in a consortium for Shoreside Power from Optimised Hydrogen Lifecycle (SPOHL). We are seeking a skilled researcher to lead our efforts in modelling and optimizing energy systems within port environments, with a focus on renewable energy integration, grid management, and hydrogen storage. The ideal candidate will possess expertise in mathematical modelling, simulation techniques, and optimization algorithms, coupled with a strong understanding of energy systems dynamics and renewable energy technologies. 

The appointee will be expected to:

1.         Develop advanced mathematical models and simulations to represent the energy infrastructure of port facilities, including renewable energy sources, grid infrastructure, and hydrogen storage systems.

2.         Utilize optimization techniques to analyse and optimize energy flows within the port, considering grid constraints, energy demand profiles, and vessel refuelling requirements.

3.         Collaborate closely with stakeholders to gather data, understand operational constraints, and validate model assumptions.

4.         Evaluate the performance of various energy management strategies through simulation and sensitivity analysis, identifying optimal solutions that balance environmental sustainability, operational efficiency, and economic viability.

5.         Implement algorithms and decision support tools to automate energy management processes and support real-time decision-making.

6.         Stay abreast of emerging technologies and best practices in energy systems modelling, renewable energy integration, and grid optimization, incorporating new findings into modelling frameworks.

7.         Communicate research findings, model validation results, and optimization recommendations to technical and non-technical audiences through reports, presentations, and technical documentation. 

The successful candidate will be able to demonstrate some essential characteristics: a PhD degree (or be near completion for the Research Assistant role) in Electrical Engineering, Energy Systems, Applied Mathematics, or related field with a focus on modelling and optimization; demonstrated expertise in mathematical modelling, simulation techniques, and optimization algorithms, with experience in energy systems modelling preferred; proficiency in programming languages such as Python for model development and simulation purposes; strong understanding of energy systems dynamics, renewable energy technologies, and grid integration challenges. 

For further information, please contact Dr Ioana Pisica on ioana.pisica@brunel.ac.uk

 

Closing date for applications: 20 May 2024 

For further details about the post including the Job Description and Person Specification and to apply please visit https://careers.brunel.ac.uk 

If you have any technical issues please contact us at: hrsystems@brunel.ac.uk 

Brunel University London is fully committed to creating and sustaining a fully inclusive workforce culture. We welcome applicants from all backgrounds and communities, we particularly welcome applicants who are currently under- represented in our workforce.