PhD Robotics & AI Internship — Real-World Robot Learning

Cambridge Consultants; United Kingdom; On-site; GBP 20,000 - 27,000; Full time

Job summary

Cambridge Consultants offers an exciting robotics and robot learning internship in the AI & Algorithms team. This paid placement (6–12 months) suits final-year PhD students seeking industry experience with a view to transitioning into an industry role after graduation.

You will work on a range of projects, from data collection and model training to deployment on real hardware, using cutting-edge labs and resources across healthcare and industrial applications.

Qualifications

• Final-year PhD student in robotics, computer science, AI/machine learning, or related computational discipline.
• Hands-on experience across the full pipeline from data collection to real-world deployment.

Responsibilities

• Build and deploy robot learning systems from data collection through to training and real-world deployment.
• Integrate robot hardware and software, enabling perception, learning from data, and reliable action.
• Support client projects applying robotics and AI to healthcare and industrial settings.
• Learn software & systems engineering in mixed-discipline teams and contribute to planning sessions.
• Contribute to internal research programs, building on state-of-the-art robotics literature for market-leading solutions.
• Communicate results to colleagues and clients.

Skills

Publications in leading venues

Data collection & deployment

Mechatronics understanding

Python & C++

Git & software engineering

Education

PhD student in robotics/CS/AI/ML

Tools

ROS

Simulation tools

Python

C++

Git

Job description

Cambridge Consultants offers an exciting robotics and robot learning internship in the AI & Algorithms team. This paid placement (6–12 months) suits final-year PhD students seeking industry experience with a view to transitioning into an industry role after graduation.

You will work on a range of projects, from data collection and model training to deployment on real hardware, using cutting-edge labs and resources across healthcare and industrial applications.