Research Associate in Deep Learning for Computational Lightfield Microscopy

About the role:

Applications are invited for the above post to work with Professor Christos Bouganis and his team at Imperial College London for a Wellcome Trust funded project.

The successful candidate will be integral to delivering on the project called “Optical Oscilloscope: Real-time, High-throughput, Volumetric Voltage Imaging.” Our goal is to enable real-time, kilohertz, volumetric voltage imaging in 1,000 cells simultaneously within scattering mammalian brain tissue.

The successful candidate will research and develop a computational platform based on GPU and FPGA devices that would accelerate the execution of deep neural networks designed by the rest of the team for volume reconstruction from lightfield video sequences produced by our lightfield microscope.

What you would be doing:

You will design, build and optimize a platform based on GPUs and FPGAs that aims to accelerate the computation of new model-based deep neural networks (DNN) for real-time neural activity extraction from lightfield microscopy data. You will research and build the infrastructure that would enable the communication of the CPU-GPU-FPGA subsystems, in order to achieve low-latency and high-throughput. You will investigate and implement strategies for the mapping of the DNN architectures for volume reconstruction developed by the rest of the team to the available computational platforms in order to minimise the latency of the computation. You will also consider the optimisation of the DNN models by investigating different quantisation methods taking into account the available hardware resources.

You will also work with postdoctoral associates in EEE and Bioengineering to develop algorithms for volume reconstruction that can be efficiently mapped into hardware.

What we are looking for:

The successful candidate:

• Will have a PhD (or be very near completion or equivalent) in engineering, mathematics, physics, or a related topic.
• Experience with digital design techniques and familiarity in designing hardware targeting FPGAs.
• Experience in deploying hardware designs in FPGA platforms.
• Experience with programming in CUDA.

What we can offer you:

• The opportunity to form a key part of the multidisciplinary team who will innovate methods for high-throughput, volumetric voltage imaging
• Close interaction with the highly motivated and diverse team of Prof. Bouganis all working on researching hardware architectures for the acceleration of Deep Neural Networks (https://www.imperial.ac.uk/intelligent-digital-systems/)

Further Information

Professor Bouganis’ team is based at Imperial College’s South Kensington campus in the heart of London, UK. Professor Bouganis is an expert in the design of intelligent digital systems and leads the iDSL group at Imperial College (https://www.imperial.ac.uk/idsl), with a focus on the theory and practice of reconfigurable computing and design automation, mainly targeting the domains of Machine Learning, Computer Vision and Robotics. 

This full-time, in-person postdoctoral position is based at Imperial College’s South Kensington campus in London, UK and is funded for 18 months initially, starting in November 2024. In October 2025, we will compete for the Wellcome Trust scale-up phase, which could extend the project's funding for an additional 6.5 years.

If you require any further details on the role please contact: Christos Bouganis christos-savvas.bouganis@imperial.ac.uk.

If you encounter any technical issues while applying online, please don't hesitate to email us at support.jobs@imperial.ac.uk. We're here to help.

Closing date: 10/10/2024

To apply, click the 'Apply' button above.

Advert information