About Us Quantum Brilliance is the world leader in room-temperature quantum computing using synthetic diamonds. Our unique vision is to make quantum computing available as an everyday technology, from data centres to remote and mobile systems like autonomous robots and satellites. In contrast to quantum computers that fill a room, we are developing quantum accelerators in a form factor smaller than a lunchbox. Founded in 2019 by leaders in diamond quantum science from the Australian National University, we are a full-stack quantum computing company. Our HQs are in Canberra and Stuttgart, with additional locations across Australia and southern Germany. We are working with global technology leaders to develop quantum computing applications, integrate quantum with high-performance computing, solve materials science challenges and develop ultra-precise semiconductor manufacturing and quantum control techniques. We are backed by leading venture capital funds and major research and technology institutes. The Mission We are looking to hire a Machine Learning Researcher to join our Quantum Utility Exploration (QUTE) team in Stuttgart, Germany. As an integral part of the QUTE team, you will help to establish the utility of diamond-based quantum systems. For this, you will develop both classical and quantum machine-learning algorithms that demonstrate the utility of diamond-based quantum computing, and collaborate with quantum algorithm, hardware, and control specialists. Core Responsibilities As an integral part of the QUTE team, you will be responsible for Machine-learning-oriented algorithm research for NV-based quantum computing paradigms, such as reservoir and neuromorphic computing on gate-based, analogue, and hybrid quantum computers; Development and extension of our quantum machine learning software towards edge computing (e.g. through quantization & quantization-aware training) and/or parallel quantum acceleration; Collaboration on the development and optimization of machine-learning based quantum control and readout algorithms; Close monitoring of state-of-the-art literature and developments as well as frequent visits to scientific conferences; Collaborate with an international team in Australia and Europe. About You PhD in computer science, physics, chemistry, computational biology or similar fields (strong emphasis on algorithms/simulations); 5 years of experience in machine learning; experience in robotics/automation would be beneficial; Coding experience with Python and C++; Experience with professional software development tools such as git (CI/CD and cmake desirable); Experience with hybrid work models, and willingness to partially collaborate in-person. Working at Quantum Brilliance At Quantum Brilliance, you will join a team of experts working to create massive, transformative impact. You will join a team of problem-solvers, who are curious and driven to understand and master new things. We pride ourselves on a collaborative environment, where we learn from the unique expertise that each person brings, and support the growth of each team member. Collaborating with colleagues around the world: We currently have labs in several locations across Australia and Germany, and collaborate with leading research institutions and quantum technology companies. You will have opportunities to travel between QB locations for knowledge exchange. Continuous learning: You are expected to keep pace with the state of the art in the field. If you are switching fields, you will need to rapidly get up to speed with the literature history, something we will help with but that you are expected to drive. There are further exciting learnings in project management, team leadership, and business operations. Research leadership: As you complete projects and build your understanding of the company and its R&D programs, you will be increasingly expected to provide input to help shape roadmaps and targets for subsequent R&D projects. This can include pitching projects to follow-up on discoveries made during previous projects. Give back: you will have plenty of opportunities to share your knowledge within the team. This can include providing technical leadership and mentoring to other team members, doing projects with brilliant interns, and regular internal technical group meetings.