Emulate Energy is a startup, founded in 2020, with a mission to accelerate the transition to clean energy. A big hurdle towards the transition has been the ability to store energy. We have developed an algorithm which emulates a physical battery by using flexibility in electricity demand. This means that we tackle the issue of energy storage without the need for a physical battery and the associated raw materials and maintenance.
Our software solution coordinates the electricity use of household devices, such as air conditioning, heat pumps, and electric vehicle chargers. These units have some flexibility in when they use electricity, and through proper coordination, they can collectively mimic a single, well-understood battery. This virtual battery can then be used to balance renewable energy production and support electrification of transportation and heat. (The solution is a spin-off from academic research. A brief overview is given here https://news.mit.edu/2017/virtual-batteries-cheaper-cleaner-power-0324 )
We are looking to strengthen our research team with up three new members.
As a modelling engineer you are an integral part of the research team. Your work on modelling, online system identification, and predicting the power draw of electric devices, both standalone and in aggregate. You also use your modelling results to create simulation environments for the entire research team.
You are part of the whole solution cycle, meaning that you formulate problems, derive solutions, and implement them on our cloud platform. We help each other by reviewing each other’s work and jointly tackle problems that arise in regular team meetings. We use an iterative approach to problem solving, where we continuously build, measure, and learn in shorter iterations.
Apart from technical work, you are expected to act as a subject matter expert in client meetings and conferences.
A little about you:
You have an MSc. or preferably PhD, control theory, statistics or similar. You have an excellent understanding of dynamical systems and data-driven modelling, and good knowledge of statistics. Experience with grey-box identification is a plus.
You have excellent problem solving skills and are self-reliable, meaning that you have the ability to structure your work independently without much guidance.
Most importantly, you are passionate about using your skills to make the world a better place
