ICT Ignite - Web Dev - Front end user interface for existing back-end utilities.

Qoherent has produced a set of command line utilities for performing machine learning dataset curation and model training that can be useful as the back end for a web application. The project's goal is to create a user interface with a user-friendly UX for a web application based on these command line tools with a good user experience. This project requires no knowledge of machine learning, but learners will get some exposure to ML and have the opportunity to contribute to a a web-based design tool.

Product management for software defined radio within satellite communications

Who we are: Qoherent is driving the creation of intelligent radio technologies. Intelligent radios integrate machine learning-based signal processing to build more robust, aware, and adaptive radiofrequency (RF) communications and sensing systems that generally out perform traditional radio systems. Qoherent creates data-driven solutions using machine learning techniques for passive sensing of the RF spectrum to identify and analyze signals such LTE, 5GNR, and more. Our product offering includes application-specific IP composed of datasets and models, as well as design tools that help engineers bridge the knowledge gap between the RF and ML domains. Qoherent also investigates applications of quantum machine learning as applied to real-world RF problems. Project overview: Qoherent is investigating offering its services into the satellite communications industry. This project is an investigation into the applications of software-defined radio in satellite communications which will feed into Qoherent’s product planning efforts. The outcome of this project may impact our hardware development plans as well as our software development plans. Our goal is to understand how software-defined radios are in the satellite communications industry. This project is suited to computer engineering, electrical engineering, computer science, or systems engineering students who wish to pursue a career in hardware product management. Qoherent aims to understand: Use-cases for software-defined radios within satellite communications The workflow of these use cases. Technical challenges and limitations. Algorithms and implementations of software that are currently used in the industry in space and on the ground. Technical specifications, costs, power constraints Challenges and opportunities for the use of AI within satellite communications networks (on the ground or in space) We hope to use findings gathered in the project to inform future plans for product development, R&D, and positioning. We would like students to complete a project with product management and customer discovery activities such as: Reviewing the landscape of existing public satcom and cube sat companies to understand how they are positioned, how they use software-defined radio, and how those radios may have been designed. Conducting interviews with technical stakeholders across the satellite communications value chain to discuss applications of software-defined radio in the industry. Reviewing relevant published works (e.g. IEEE proceedings) Categorize and summarize findings into user stories Qoherent will begin the project with an orientation of its current business, and its plans for satellite communications, and any necessary coaching to complete the project. Qoherent will also provide a starting point for industry stakeholders to speak to. Other details: Number of students required: Up to a team of 3 students, but individuals will be accepted. Commitment: Up to 80 hours per student for the duration of the project Scope: A presentation, an executive summary, a written report and any appendixes that outline findings of the project.

Illustration and animation assets for an AI start-up.

Positions available: up to 3 Who we are: Qoherent is an early-stage start-up that is driving the creation of AI-based radio technologies. Qoherent provides solutions and a platform for integrating machine learning into software-defined radios, for the purpose of building robust, aware, and adaptive radio communication systems. Qoherent’s current focus is on providing customers with software solutions for recognizing wireless activity with machine learning, as well as building a platform of software development tools to aid in creating machine learning models, deployable to heterogenous systems, that recognize radio waves. Our goals for this project: We need brand-consistent visuals that describe our technology, to use in our powerpoints, literature, and website - in short, we need illustration and animation help! We are looking for teams that can help amplify what makes us unique and create better visual messaging for our brand. The objective is to create brand-consistent images that help us communicate our message. This project may combine research, data analysis, graphic design, illustration, animation, prototyping, and more! We are agnostic to the tools used by the students. We will give you access to organizational assets (existing decks, visuals, mock-ups, and wireframes), our brand guidelines, and our time to support this project. We can also suggest names of competitors and comparators to research. Other details: Number of students required: Up to a team of 3 students, but individuals will be accepted. Commitment: Up to 80 hours per student for the duration of the project Scope: The number of visual assets to be made will be defined to meet the size of the team, and will be discussed as part of the project.

backlog management process improvement for a startup

Qoherent is looking for a student intern to set up a system for managing our software development backlog and roadmap. The student would take Qoherent’s desired feature list and translate it into a manageable and prioritized backlog in a tool such as Linear or Jira. A successful project would result in Qoherent’s team of developers having a well curated and organized backlog, as well as a repeatable and measurable process for managing it.