AI Thesis collaboration: Develop and implement 'Active Learning'

Introduction

We are a hardware (IoT) and AI climate tech startup founded in 2022 on a mission to completely digitize homes to help eliminate all energy waste and make homes safer through unprecedented transparency.

Our combined hardware-enabled AI solution disaggregates the total electricity consumption down to each individual device in real-time, opening up new ways for homeowners to understand their homes.



We are backed by an early-stage VC and a group of strategic business angels with impressive exits to companies like Oculus/Facebook/Meta, Bain & Company, and EQT. With Float you get a fun and friendly app for every homeowner. Think of it as the Apple Health app but for your home’s well-being.



The Topic

To scale a solution like ours to thousands of homes, we need users to be able to verify or override what our current AI model thinks is a specific device or appliance. Therefore, we need to develop an "active learning" component in our pipeline.



We would like, together with you, to define an MVP solution of how such a component could work, look and function.

In the project, it is essential that the component can be implemented in the existing pipeline and be tested rigorously. This will partly be done in collaboration with the Float team.



We understand that there needs to be a scientific approach included in your thesis and we are very open to various suggention here. About you

We are looking for students with a strong mathematical background and interest. You could be studying Mathematical Modelling, Data Science, Computer Science, related fields of Engineering etc.



We are open to collaborate with students from all universities offering masters degrees in these fields of studying.

All or some of these attributes describe you:

• Genuine desire to work with AI after graduating
• Interest in time series data.
• First principle thinking problem solver
• Entrepreneurial mindset



If this sounds like you, then we can offer a unique opportunity to work with a vast amount of proprietary data and the chance to build and scale a custom end-to-end AI solution. In addition to the AI team, we also have an Embedded Software team and a Back-End team.



In short, we are looking for students with drive, high degree of intellectual curiosity, eagerness to acquire unique hands-on experience and a desire to work on impactful solutions that will delivery real results in real life settings. By taking on this project you will also have the potential of joining a highly ambitious and growing hardware and AI climate tech startup.