Research Assistant or Associate in AI Model Optimisation for Edge Devices & NVIDIA Holoscan Sen[...] in London

We are seeking a Research Assistant or Research Associate to work at the intersection of AI model optimisation, GPU kernel development and FPGA-based hardware integration. The project targets the seamless integration of computer vision FPGA-based IPs with NVIDIA's Holoscan Sensor Bridge - a cutting-edge technology enabling low-latency, high-throughput streaming between sensors and edge GPU platforms.

The project involves Imperial College London and an industrial partner, Heronic Technologies, aiming to revolutionise the "Sense-Decide" pipeline in edge automation. You will contribute to building a system that tightly couples custom FPGA-based AI-ISP accelerators with NVIDIA's GPU-powered edge platforms, with a focus on minimising latency while maintaining high performance and scalability. A significant part of the work will involve AI model optimisation and the customisation of edge GPU kernels to push system performance to its limits. This is a genuinely multidisciplinary challenge, spanning AI model design, low-level GPU kernel engineering, and hardware-software co-design - an opportunity to advance the state of the art in how AI signal processing systems are built and deployed.

What you would be doing:

• Investigating and developing system architectures that demonstrate low-latency, easy integration of custom AI-ISP accelerators with GPU platforms via NVIDIA's Holoscan Sensor Bridge.
• Developing and evaluating the full system under object detection applications, assessing performance across latency and detection accuracy metrics.
• Implementing models in machine learning frameworks (e.g. PyTorch) and applying hardware-aware efficiency metrics to evaluate energy, memory, and latency trade-offs.
• Contributing to research publications and presenting results at academic conferences.
• Collaborating closely with Prof Christos Bouganis and the team at Heronic Technologies, who are developing the FPGA-based AI-ISP accelerator.
• Helping to bridge the gap between academic research and industrial impact in energy-efficient AI.

What we are looking for:

• A strong background in GPU programming, machine learning, digital hardware design, computer engineering, applied mathematics, or a closely related field.
• Experience with software engineering for scientific computing or machine learning (e.g. PyTorch), GPU programming and/or digital hardware design (e.g. Verilog).
• Ability to analyse complex systems, develop new models, and communicate research clearly.
• A collaborative mindset and genuine enthusiasm for advancing energy-efficient AI.
• An interest in one or more of the following areas is desirable:
• Efficient machine learning and AI model optimisation.
• GPU kernel programming and optimisation.
• Digital hardware or FPGA architectures.

Qualifications:

• Research Associate: A PhD in machine learning, computer engineering, applied mathematics, or a closely related discipline -- or equivalent research or industry experience.
• Research Assistant: A master's degree (or equivalent) in a relevant discipline -- or equivalent experience. Candidates who have not yet been officially awarded their PhD will be appointed at Research Assistant level.

What we can offer you:

• The chance to work on cutting-edge research in low-latency and energy-efficient AI, tackling real challenges in sensor-to-GPU integration at the hardware-software boundary.
• A highly active research environment within the Department of Electrical and Electronic Engineering at Imperial College London, with experts in machine learning, GPU programming, and digital hardware design.
• Hands-on experience with algorithm-hardware co-design, including AI modelling, efficient ML methods, and GPU-based optimisation.
• The opportunity to develop research publications and contribute to an emerging and industrially relevant research direction.
• Access to Imperial's sector-leading career development support, including training, mentoring, and opportunities for progression.
• A competitive salary and benefits package, including 39 days of leave per year and a generous pension scheme.

This is a fixed-term position for up to 17 months (subject to probation), based in the Department of Electrical and Electronic Engineering at Imperial College London.

Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.

We reserve the right to close the advert prior to the closing date stated, should we receive a high volume of applications. It is therefore advisable that you submit your application as early as possible to avoid disappointment.

If you encounter any technical issues while applying online, please don't hesitate to email us. We're here to help.

About Imperial: Welcome to Imperial, a global top-ten university where scientific imagination leads to world-changing impact. Join us and be part of something bigger. From global health to climate change, AI to business leadership, here at Imperial we navigate some of the world’s toughest challenges. Whatever your role, your contribution will have a lasting impact.

As a member of our vibrant community of 22,000 students and 8,000 staff, you’ll collaborate with passionate minds across nine London campuses and a global network. This is your chance to help shape the future. We hope you’ll join us at Imperial College London.

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