Computer Scientist Position

Location: Hybrid

Contract Type: Permanent

Salary: negotiable based on exprience

Company Description

Energy Reform engages in research and consultancy in the international energy sector and has specialist expertise in developing and applying state of the art power system and energy system modelling techniques in support of the energy transition.

Energy Reform was born in 2011 out of the leading-edge research at the Electricity Research Centre, headed by Professor Mark O’Malley at University College Dublin and has built a global reputation for applying leading edge research in the area of renewables and energy system integration to the real challenges of modelling the transition to green energy and net-zero carbon emissions. Energy Reform has deep expertise in carrying out complex energy system modelling tasks with diverse aims and objectives in support of the energy transition including notable expertise in the areas of variable renewables, long term storage, hydrogen and Power to X.  At Energy Reform, we are modellers and model developers and possess the skills to implement advanced methodologies that often require bespoke developments to satisfy clients’ specific requirements.

Additionally, Energy Reform is a recognised expert internationally, participating in the International Energy Agency’s Task 25 on the Design and Operation of Power Systems with Large Amounts of Wind Power and is a member of the Global Power System Transformation Research Council. Energy Reform is a key contributor to the open-source Spine energy system modelling framework

For more information see


This is an opportunity for an enthusiastic qualified computer scientist who is hungry to develop their career in a dynamic and growing company having a real impact on the energy transition. We develop and apply state-of-the-art open-source tools to address the complex challenges of modelling the energy transition and to explore the role flexible technologies can play. Our client base is international, and this is a valuable opportunity to be involved at the leading edge and have a real impact on shaping the future energy system.

Key Responsibilities

  • Maintaining and developing the Spine code base.
  • Leading the development of new features/components or critical bug-solving, including documentation and testing.
  • Be a commercially astute computing/data science professional with a high level of technical competence
  • Proficient in data manipulation of large datasets through the use of analytical tools (e.g. Tableau, SQL, VBA, Python, R) and a willingness to learn new languages
  • You will build models which can run in the cloud or onboard an instrument which will enhance the capabilities of our world-class energy solutions portfolio
  • Creating, building and maintaining analytical tools through programming to generate insight, recognize trends / patterns
  • Developing and delivering programming initiatives that increase automation and enhance testing
  • Experimenting and identifying with various analytical methods / techniques
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Responding to ad-hoc requests and communicate the results of any analysis and trends
  • Proven presentation and communication skills

Required Qualifications, Experience and Competences

  • Experience in collaborative software development
  • Highly motivated and adept to working with remote teams using online collaborative tools
  • Documentation, testing.
  • Multiple programming paradigms (OOP, declarative, multiple dispatch, metaprogramming)
  • Proficiency in the git version control system. Experience in continuous integration.
  • Proficiency in SQL, Python and Julia, with proven ability to use advanced language features.
  • Proven capacity to solve issues and respond to users’ needs. Ideally, they have participated in the development of an application that has active users.
  • Proven capacity to interact and blend with the work of other programmers.
  • Front-end and back-end.
  • Degree educated in Mathematics, Statistics, Computer Science, Data Science or Engineering, preferably a PhD
  • Proficiency in Scientific programming languages
  • Experienced in modelling techniques
  • A proven track record with 3+ years of experience in data science in commercial environments
  • Pragmatic versatile self-starter: a dynamic over-achiever with a curious mind and a thirst for new challenges
  • Possess an analytical mind:
  • Experience in scientific or engineering fields
  • An “anything is possible” mentality: we aim high!
  • Experience working in an Agile environment with cross-functional teams.
  • Knowledge and experience of power and/or energy system modelling is highly desirable
  • Knowledge of linear and mixed integer optimisation and experience of developing optimisation models is desirable

Test Power System Distribution System Network Data in Spine

Paul Cuffe and his team at University College Dublin have developed a number of really useful distribution tests systems which can be used in power system research. We have converted these to Spine format so they can be visualised and used within the Spine open-source energy system modelling framework.

Visualizing the energy system can be very useful to gain insight and spot issues, but also challenging from a computational point of view. In the Spine Project, we have developed a special tool called Spine Database Editor that (among other things) allows you to visualize your data as a graph of objects and relationships. Below are some examples from a few of the test power distribution networks developedhere.

Our algorithm is based on the seminal work by Paul Cuffe and is optimized to make use of vector machine instructions for a nice speedup.

We have converted the tests systems to Spine format and have made these available via a Spine Toolbox project. Some sample layouts are show below which were generated using Spine Datastore Editor.

Additionally, you can find the converted Spine sqlite files here.

Reference to original journal article: M. Mahdavi, H. H. Alhelou and P. Cuffe, “Test Distribution Systems: Network Parameters and Diagrams of Electrical Structural,” in IEEE Open Access Journal of Power and Energy, vol. 8, pp. 409-420, 2021, doi: 10.1109/OAJPE.2021.3119183. Available online here.


Spine Webinar Capture

Spine Webinars Available

As the H2020 Spine Project draws to a close, we have held our final series of webinars. Over the last 4 years the Spine project consortium has developed a uniquely flexible and capable Energy Systems Modelling Framework.