Master Thesis: Quantum randomized navigation for autonomous enterprise robots

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About this opportunity

We are seeking a Master’s thesis student to investigate how stochastic navigation and route selection can be implemented using output from a quantum random number generator (QRNG). The robot will identify multiple feasible routes and use QRNG-generated randomness to select among them, while ensuring that safety, accessibility, and operational constraints are always respected.

Enterprise IT departments increasingly manage large inventories of mobile phones and other equipment. A mobile robot could support the internal logistics process by receiving a retrieval order, navigating to the correct storage location, collecting a phone, and delivering it to an IT employee at the service desk. The thesis will provide an experimental assessment of how QRNG-generated randomness can be incorporated into autonomous robot navigation in an enterprise setting. It will clarify where QRNG offers a meaningful benefit, where conventional pseudorandomness is sufficient, and how stochastic behaviour can be implemented without compromising safety, reliability, or operational accountability.

What will you do?

In this thesis, you will study, design, implement, and evaluate a safe stochastic navigation system in which QRNG output influences the robot’s route-selection decisions. Your work will include: study and select a route-selection algorithm, evaluate under which conditions does stochastic route selection improve navigation performance, and also benchmark if a QRNG based route selection can reduce congestion, repeated path usage or predictable robot behaviour compared to a deterministic pseudorandom approach. You will also configure a mobile robot to operate in the office environment and integrate with a QRNG.

The skills you bring:

• Enrolled in the final year of an MSc program in Robotics and autonomous systems, Electrical engineering, Engineering Physics, Computer Science or a closely related field.

• Strong programming skills in Python. Experience with ROS or C/C++ is an advantage.

• Familiarity with machine learning, robotics frameworks, indoor localization.

• Interest in edge AI, embedded systems, physical AI, robotics, or intelligent sensing.

• Basic understanding of probability, random number generation, and statistical evaluation.

• Proficient in spoken and written English.

• Ability to work independently, manage a 20-week research project, and communicate findings clearly in writing and presentation.

• Ability to design and conduct experiments, analyse performance results, and draw clear technical conclusions.

• Good communication skills and the ability to work independently as well as collaboratively.

Why join Ericsson?

At Ericsson, you will have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what is possible. To build solutions never seen before to some of the world’s toughest problems. You will be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.

Encouraging a diverse and inclusive organization is core to our values at Ericsson, that' is why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer.