Job Description
We are seeking an ambitious, analytical and motivated individual to lead an exciting and innovative Knowledge Transfer Partnership (KTP) project between Zenergy Solar Ltd. and the School of Built Environment, Engineering and Computing at Leeds Beckett University.
This 28-month KTP project will focus on the design and implementation of the ZenSmart platform, embedding advanced AI and real-time data analysis to optimise the delivery of solar energy solutions through improved system efficiency, diagnostic and fault resolution.
The Role
Supported by a comprehensive project plan and working in partnership with academics from Leeds Beckett University and the team at Zenergy, you will
- Work across PV, energy storage and power electronics, designing intelligent, fault tolerant system architectures and control strategies.
- Develop scalable backend systems and integrate internal and third party platforms to support multi site operations and diverse datasets.
- Enhance battery modelling, data handling and grid service optimisation through cloud technologies, real time analytics and embedded AI.
- Create user friendly tools for both technical and non technical users while managing inverter communication protocols and analysing fault scenarios (e.g., Modbus, SunSpec).
- Operate a controlled test rig for experimentation and simulated faults, and contribute to industry knowledge through documentation, training and wider collaboration.
The Company
Zenergy Solar build and supply tailored solar and storage solutions with an emphasis on optimised battery storage and integration with the national grid, designed to maximise efficiency and reduce costs. With over 20 years’ renewable energy experience, they provide end-to-end project management, from site survey and bespoke design through to turnkey installation and ongoing maintenance.
The Person
We are looking for candidates with a robust academic background, holding at least a 21 degree in Computer Science, Electronic/Electrical Engineering, or a closely related discipline. A higher degree in renewable energy systems, AI, or embedded systems would be advantageous.
Applicants should also demonstrate
- Proficiency in programming languages such as Python, JavaScript, C++, and MATLAB.
- Strong technical writing skills, with the ability to produce clear, concise, and well-structured documentation and reports.
- Experience with data processing pipelines, cloud platforms, and API integration.
- Understanding of photovoltaic systems, battery storage, and power electronics.
- Experience in AI and machine learning (ML) methods for predictive modelling.
Experience with microservices, containerisation (e.g., Docker), and communication protocols (e.g., Modbus, SunSpec) is desirable.
You will work in collaboration with an engaged and forward-thinking team at Zenergy as well as a team of academic experts from Leeds Beckett University through the acclaimed Knowledge Transfer Partnership (KTP) programme. This is an invaluable opportunity to fast-track your career development, gain senior-level experience, and establish your position as an industry leader in applied technology and innovation.
To support your development, you will benefit from a management training programme and a generous personal development budget.
There may also be the opportunity for the successful candidate to study for a higher degree (MRes, MPhil, or PhD) with a fee waiver.
Information Session
We will be holding an online information session on Wednesday 18th February, from 2-3pm, where we will provide information about the role, the project, the company partner and about KTP. You will also be able to ask questions about the position.
Please book via Eventbrite https//www.eventbrite.com/e/ktp-information-session-smart-energy-systems-engineer-at-zenergy-solar-ltd-tickets-1982009189841?aff=oddtdtcreator
Should you require any further information about this post, please contact Laura Forester-Green ( l.t.forester-green@leedsbeckett.ac.uk ) or Dr Akbar Sheikh Akbari ( a.sheikh-akbari@leedsbeckett.ac.uk) .
Closing date Thursday 26th February (23.59)
Interview date First interview scheduled for 16th March, Final interview scheduled for 23rd March (These may be subject to change)
Working here means you’ll also have access to a wide range of benefits including our generous pension schemes, excellent holiday entitlements, flexible working, reduced study fees, subsidised fitness facilities and a lot more.
We welcome applications from all individuals and particularly from black and minority ethnic candidates as members of these groups are currently under-represented at this level of post. All appointments will be based on merit.
Apply online
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