Research Associate in Data-driven Methods for - Cardiff, United Kingdom - Cardiff University

Cardiff University
Cardiff University
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Cardiff, United Kingdom

2 weeks ago

Tom O´Connor

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Tom O´Connor

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Research Associate in "Data-driven methods for energy systems modelling and optimisation"

Cardiff University School of Engineering- 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.- 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

Opening date: 24 August 2023

Closing date: 10 September 2023

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


Main Function


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

Research

  • To conduct research in the area of Spatial and temporal estimation of energy demand, and Physicsaware Machine Learning methods for optimisation of integrated energy networks. In addition, the postholder 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 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

Other

  • 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.

Person Specification

Essential Criteria

Qualifications and Education

  • Postgraduate degree at PhD level in Engineering, Physical Science, Operation Research, Statistics and computer science, or relevant industrial experience.
    Knowledge, Skills and Experience
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
  • Competency in Python programming and large-scale model development is essential
  • 4. Knowledge of cu
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