Recruiting

Company Profile

Informetis Europe, based in Cambridge, is a subsidiary of Informetis Company Japan, which itself is a spin-out from what was previously Sony Corporation’s R&D Energy Division. Our company name Informetis means “Goddess of Information”. The energy industry has the potential to transform itself exponentially based on new information. With the expansion of renewable energy, power generation is undergoing major changes, which increasingly requires detailed and meticulous control management. We contribute to a sustainable planet by applying rapidly-evolving network and AI (machine learning) technologies to energy data, and developing an ecosystem that delivers both efficient energy use and improved Quality of Life (QoL).

Our first solution aims at saving electricity cost and improving the flexibility of the energy system. By raising user awareness and suggesting optimal running time, homeowners can reduce their electricity bill with our cloud based service which uses a single clamp electricity sensor providing an itemised view of their electricity bill. We are also working on smart home energy management with a heat pump and other high power consumption appliances in order to reduce the carbon footprint and save energy costs for the user.

Our second solution enables the elderly to stay for longer and independently in their own homes. We provide 24/7 unobtrusive monitoring of the elderly relative/friend (‘caree’) by their own family members (‘carer’). Part of this service is to provide notifications and alerts of ‘unusual behaviour patterns’ to carers about their carees.

Job Description

As part of a multinational machine learning team, you will apply your machine learning knowledge as well as coding skills to help develop our unique NILM (Non Intrusive Load Monitoring) technology. By applying machine learning classification, regression, and clustering techniques, you will help develop algorithms to analyse electricity data. In particular, you will analyse electricity waveform data, create algorithm concepts and code, test and evaluate them in Python. You will also apply statistics and analytic skills to further improve this system and develop new data-driven smart energy services.

This role will involve modelling domestic electric appliances using our collected data, adapting our existing in-house state-of-art NILM algorithms to different markets, and applying unsupervised learning methods to extract patterns and detect anomalies within our analysed data. There will be opportunities to conduct novel research and to propose new projects. You would also have the opportunity to work on time series predictive modelling as well as reinforcement learning to design optimal control for home energy management systems.

Candidate Profile

This role is suitable for PhDs in STEM subjects. Because we are a start-up, you will be part of a motivated and talented team with a very friendly and helpful culture, known for its out-of-the-box thinking!

You would be provided time and monetary resources for self-learning and professional development. There is also support from external academic advisors. In addition, there are opportunities for learning and applying novel techniques to real world business problems. As our company expands, there will be opportunities to take more responsibility and lead projects and teams.

We are also looking for part time or interns who would like some real world experiences with machine learning.

Required skills:

• • Experience in applying Machine Learning techniques to novel problems and datasets

  • Passion to learn the latest machine learning technologies

  • Experience in independent research

  • A PhD degree in STEM subjects

Recommended skills:

• Good knowledge of Machine Learning fundamentals

• Experience in implementing Machine Learning algorithms in Python

• Good coding skills in Python and practical experience

• Ability to conduct independent research and read academic paper

• Experience in anomaly detection, time series analysis, and regression techniques

• Pandas, Numpy, Sklearn, and Scipy

• Experience with assisted living

• Experience with grid demand response or home smart energy management system

Benefits:

• Flexible working hours

• Options for remote working

• On-site parking

• Company events & social hours

• Sick pay

• Casual dress code

• Professional development

To Apply

If you are interested in applying for this job please send your CV and a covering letter (optional) to jobs@informetis.com