Research Associate in “Data-driven methods for energy systems modelling and optimisation”
Cardiff University School of Engineering
We seek to recruit a highly motivated Research Associate with proven intellectual and technical ability to conduct research in the area of modelling energy supply systems and energy demand. The candidate will contribute to an on-going research activities in CIREGS (Centre for Integrated Renewable Energy Generation and Supply) that concern (1) estimating temporal and spatial energy demand (e.g. electricity, heating and cooling) in buildings in the UK under selected decarbonisation scenarios, and (2) developing physics-aware Machine Learning methods for optimising the operation of integrated energy networks.
An ideal candidate would be a self-starter and a resourceful team-player with an appetite for working with the industry. The successful candidate will also contribute to the overall research performance of the School and University, carrying out research leading to the publishing of work. To pursue excellence in research and to inspire others to do the same.
This post is full time, 35 hours per week, available immediately and is fixed term for 24 months, until 31 August 2025. The post is externally funded by the EPSRC.
The prospective candidate will become a member of the CIREGS research group within the School of Engineering. CIREGS leads and is involved in a number of large research and development projects in the UK.
A research associate will further benefit from an opportunity to attend award-winning courses, workshops and careers advice organised by Cardiff University specifically aimed at researchers throughout their career to develop research and professional skills.
Salary £39,347 – £44,263 per annum (Grade 6). It is anticipated that the appointment will not be made above point 32, £39,347 per annum.
Job ref: 17233BR
For informal enquiries about the post please contact Professor Meysam Qadrdan ([email protected]).
For further details about working at Cardiff School of Engineering please contact Chiara, [email protected]
The School of Engineering holds an Athena SWAN Bronze Award that recognises good employment practice and a commitment to develop the careers of women working in science. Cardiff University is an equal opportunities employer and positively encourages applications from suitably qualified and eligible candidates regardless of sex, race, disability, age, sexual orientation, gender reassignment, religion or belief, marital status, or pregnancy and maternity. For this vacancy we actively encourage women to apply. We will also consider proposals for flexible working or job share opportunities.
Opening date: 24 August 2023
Closing date: 10 September 2023
Please be aware that Cardiff University reserves the right to close this vacancy early should sufficient applications be received.
Cardiff University is committed to supporting and promoting equality and diversity and to creating an inclusive working environment. We believe this can be achieved through attracting, developing, and retaining a diverse range of staff from many different backgrounds. We therefore welcome applicants from all sections of the community regardless of sex, ethnicity, disability, sexual orientation, trans identity, relationship status, religion or belief, caring responsibilities, or age. In supporting our employees to achieve a balance between their work and their personal lives, we will also consider proposals for flexible working or job share arrangements.
Cardiff University is a signatory to the San Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions we will evaluate applicants on the quality of their research, not publication metrics or the identity of the journal in which the research is published. More information is available at: Responsible research assessment – Research – Cardiff University
To conduct research within Spatial and temporal estimation of energy demand, and Physics-aware Machine Learning methods for optimisation of integrated energy networks and contribute to the overall research performance of the School and University, carrying out research leading to the publishing of high-quality research. To pursue excellence in research and to inspire others to do the same.
Main Duties and Responsibilities
• To conduct research in the area of Spatial and temporal estimation of energy demand, and Physics-aware Machine Learning methods for optimisation of integrated energy networks. In addition, the post-holder is expected to contribute to the overall research performance of the School and University by the production of measurable outputs including publishing in academic journals and conferences, and supervising MSc and PhD students
• To define research objectives and develop proposals for their own or joint research including research writing funding proposals
• To attend and present at conferences/seminars at a local and national level as required
• To undertake administrative tasks associated with the research project, including the planning and organisation of the project and the implementation of procedures required to ensure accurate and timely reporting
• To prepare research ethics and research governance applications as appropriate
• To review and synthesise existing research literature within the field
• To participate in School research activities.
• To build and create networks both internally and externally to the university, to influence decisions, explore future research requirements, and share research ideas for the benefit of research projects
• To engage effectively with industrial, commercial and public sector organisations, professional institutions, other academic institutions etc., regionally and nationally to raise awareness of the School’s profile, to cultivate strategically valuable alliances, and to pursue opportunities for collaboration across a range of activities. These activities are expected to contribute to the School and the enhancement of its regional and national profile.
• To undergo personal and professional development that is appropriate to and which will enhance performance.
• To participate in School administration and activities to promote the School and its work to the wider University and the outside world
• Any other duties not included above, but consistent with the role.
Qualifications and Education
1. Postgraduate degree at PhD level in Engineering, Physical Science, Operation Research, Statistics and computer science, or relevant industrial experience.
Knowledge, Skills and Experience
2. An established expertise and proven portfolio of research experience within at least two of the following research fields:
⦁ Applications of machine learning and data analytics in the energy sector
⦁ Energy in buildings and energy demand estimation/forecasting
⦁ Large scale optimisation
3. Competency in Python programming and large-scale model development is essential
4. Knowledge of current status of research in specialist field
5. Proven ability to publish high quality papers in international journals / conferences and other research outputs (when it comes to publications, we prefer quality over quantity)
6. Knowledge and understanding of competitive research funding to be able to develop applications to funding bodies
Communication and Team Working
7. Proven ability in effective and persuasive communication
8. Ability to supervise the work of others to focus team efforts and motivate individuals
9. Proven ability to demonstrate creativity, innovation and team-working within work
10. Proven ability to work without close supervision
11. Evidence of collaborations with industry.
12. Project management experience
IMPORTANT: Evidencing Criteria
Candidates should evidence that they meet ALL of the essential criteria as well as, where relevant, the desirable criteria.
As part of the application process you will be asked to provide this evidence via a supporting statement. Please ensure when submitting this document / attaching it to your application profile you name it with the vacancy reference number, in this instance, 17233BR.
Academic – Research
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