At a Glance
- Tasks: Conduct groundbreaking research in Physical AI, focusing on efficient long-horizon task execution.
- Company: Durham University in collaboration with Intel, a leader in computing innovation.
- Benefits: Fully funded PhD covering tuition fees and a tax-free stipend.
- Other info: Access to advanced facilities and regular guidance from top researchers.
- Why this job: Join a cutting-edge project that shapes the future of robotics and AI.
- Qualifications: Relevant degree in computer science, AI, or engineering; strong programming skills required.
The predicted salary is between 19350 - 23650 £ per year.
Number of awards: 1
Award information: Fully funded PhD studentship covering Home tuition fees and a tax-free stipend. Available to Home fee-status applicants only due to funding structure. Delivered in collaboration with Intel, including industrial co-supervision. The student will work with Durham University academic supervisors and an Intel co-supervisor on research in Physical AI, edge AI and intelligent autonomous systems.
Closing date: 15 August
Overview: AI is shifting from passive prediction to systems that reason, plan, interact and act in the physical world. This PhD addresses efficient long-horizon task execution in Physical AI—complex tasks needing sequences of decisions, subgoals, corrections and adaptations over time. Robots must interpret instructions, decompose them, navigate dynamic environments, manipulate objects, detect failures and replan while tracking overall goals.
The core challenge is enabling high-level reasoning for long-horizon tasks without compromising the speed, reliability and efficiency required for real deployment. Current systems often reason effectively but act slowly, or act quickly but lack robust planning. Frontier models typically depend on heavy compute, cloud inference or controlled settings, limiting real-world use under compute, latency and energy constraints.
The project will explore orchestrating reasoning models, vision-language models, world models and efficient control policies for reliable robot behaviour. A key focus is deciding when to deliberate versus act reactively, using reasoning only when the gain in success justifies the cost in time, energy and compute.
Research directions may include:
- long-horizon planning with monitoring and recovery
- efficient hybrid reasoning
- vision-language task decomposition
- world models for prediction and planning
- reactive-deliberative architectures
- compute-aware evaluation
- edge/cloud orchestration
- real-robot testing
Work could involve new algorithms, reasoning pipelines, foundation model evaluation, benchmarks, platform integration and practical deployment limits. It suits candidates interested in machine learning, computer vision, robotics, efficient inference or embodied AI, prioritising practical, reliable systems.
Durham offers strong facilities: Bede HPC (128 GPU), GPU cluster (90+ GPU), LiDAR, RADAR, drones, cameras, embedded devices and robots (including Unitree G1 humanoid, quadrupeds, UGVs and aerial platforms). Intel collaboration provides industrial insight into edge AI and deployable Physical AI.
Supervision: Dr Amir Atapour-Abarghouei (Durham), Prof Toby Breckon (Durham) and Dr Samet Akcay (Intel Principal Engineer, Edge Computing). The team publishes in top venues (CVPR, ICCV, ECCV, ICML). Students receive regular guidance, research training, publication support, hardware/compute access and Intel engagement opportunities.
Entry requirements: Relevant undergraduate or master’s degree in computer science, AI, engineering, mathematics, physics or related field; strong programming skills; interest in ML, computer vision, robotics, embodied AI or autonomous systems; motivation for independent research and high-quality publications; ability to combine theory, implementation and evaluation; and meet Durham’s English language requirements. Experience in robotics, RL, foundation/vision-language models or efficient inference is desirable but not essential.
Durham University is a leading Russell Group institution in a historic North East England city with excellent quality of life. Intel leads in computing innovation for efficient, real-world edge AI and robotics.
PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (Deep learning, Computer [...] in North East employer: Durham University
Durham University is an exceptional employer, offering a vibrant academic environment that fosters collaboration and innovation. As a Postdoctoral Research Associate in Anthropology, you will benefit from extensive professional development opportunities, a supportive work culture, and the chance to contribute to impactful research that shapes understanding of diverse cultures. Located in a historic city, the university provides a unique setting for both personal and professional growth.
StudySmarter Expert Advice🤫
We think this is how you could land PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (Deep learning, Computer [...] in North East
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We think you need these skills to ace PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (Deep learning, Computer [...] in North East
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Durham University will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at Durham University
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
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Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Durham University.
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Durham University that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
