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Lecturer in Energy Systems and Data Analytics

TN United Kingdom

London

On-site

GBP 40,000 - 80,000

Full time

Yesterday
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Job summary

An established industry player is seeking a passionate Lecturer in Energy Systems and Data Analytics to join their dynamic team. This role focuses on advancing methodologies in data analytics, machine learning, and AI applications in energy management across various sectors. The successful candidate will engage students through innovative teaching methods while contributing to impactful research in sustainability. With a commitment to addressing complex energy challenges, this position offers a unique opportunity to influence the future of sustainable energy systems. If you are driven by a passion for education and research, this role is perfect for you.

Benefits

41 Days holiday
Additional annual leave purchase scheme
Defined benefit pension scheme
Cycle to work scheme
Immigration loan
Relocation scheme
On-site nursery
On-site gym
Enhanced maternity, paternity and adoption pay
Employee assistance programme

Qualifications

  • Expertise in data analytics and machine learning for energy systems.
  • Ability to produce high-quality research with publications.

Responsibilities

  • Teach data analytics for sustainable cities and buildings.
  • Collaborate with researchers to address energy and sustainability challenges.

Skills

Data Analytics
Machine Learning
AI Applications
Energy Management
Sustainability
Energy Systems Modelling
Teaching

Education

PhD in a relevant field

Job description

Lecturer in Energy Systems and Data Analytics, London
Location:

London, United Kingdom

Job Category:

Other

EU work permit required:

Yes

Job Reference:

9a794075af7d

Job Description:

About the role

The UCL Energy Institute (EI) is recruiting a Lecturer in Energy Systems and Data Analytics. The successful candidate will specialize in data analytics, machine learning, and AI applications in energy management across buildings, transport, and smart infrastructure. They will also specialize in descriptive, predictive, and prescriptive analytics, with applications in energy systems modelling, smart infrastructure, and energy management. The role requires the capacity to teach students to use data analytics for sustainable cities and buildings, focusing on machine learning and data-driven approaches across sectors and services. The candidate should have the ability to collaborate with researchers from various fields to address complex energy and sustainability challenges and demonstrate the ability to publish research in academic journals. Experience working with the energy industry, government, or NGOs on sustainability and lifecycle management of energy systems is essential. The successful candidate will contribute to teaching across our MSc and BSc programs, including Sustainable Built Environments, Energy and Resources BSc and MEng, and Energy Systems and Data Analytics. This post is available from 01st August. First round interviews will take place online on the 19th May, with second round interviews in person on the 22nd May.

About you

You will have expertise in data analytics, machine learning, and AI applications in energy systems, focusing on systems across buildings, transport, and smart infrastructure. Your research will advance methodologies contributing to energy systems modelling and energy management. You will have the capacity to incorporate modelling techniques and methods into your teaching. A demonstrated ability to produce high-quality research, evidenced by publications in peer-reviewed academic journals, is required. You will have experience working with energy industry stakeholders, government bodies, or NGOs on sustainability projects related to energy systems. You are passionate about teaching and can engage students in both theoretical and practical applications, with strong expertise in data-driven approaches to sustainable energy systems. A PhD in a relevant field that aligns with the research and teaching requirements outlined in the job description is required.

What we offer

We offer great benefits, including:

  • 41 Days holiday (27 days annual leave, 8 bank holidays, and 6 closure days)
  • Additional 5 days’ annual leave purchase scheme
  • Defined benefit career average revalued earnings pension scheme (CARE)
  • Cycle to work scheme and season ticket loan
  • Immigration loan
  • Relocation scheme for certain posts
  • On-site nursery
  • On-site gym
  • Enhanced maternity, paternity and adoption pay
  • Employee assistance programme: Staff Support Service
  • Discounted medical insurance

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