Cloud-Specific Signal and Data Processing Algorithms for Analysing Materials-Science-Specific Data

Materials Innovation Factory here at the University of Liverpool is a state-of-the-art shared scientific infrastructure, aimed at accelerating the delivery of solutions in a number of fields such as organic and inorganic materials, nanomedicines and environmental sustainability. The infrastructure houses some of the world’s best scientific platforms, such as mass spectrometers, automated formulation robots, rheometers, lumisizers, mastersizers and alike. With a very large number of experiments taking place at MIF, the facility produces massive amount of data from each sensor for a number of different configurations.

We are, in collaboration with Unilever UK and MIF, at the stage of creating a Cloud-specific, collaborative platform called Sumatra, to facilitate performing detailed data analytics on the resulting data. There are a number challenges that must be met in creating algorithms that can coexist and work with systems at MIF and Cloud while providing near real-time experience in analysing massive quantities of data.

In this project, we will develop a suite of Cloud-specific, signal or data processing algorithms that would focus on these challenges. For instance, communication avoidance, parallel and distributed formulation of algorithms, scalability, and domain-specific performance tuning and usage of deep and machine learning are some of the key challenges we will be looking into this project. To exemplify the approach, we will be using some problem-specific algorithms. The core outcomes will pave a way for engineering similar solutions across the domains.

This is an interdisciplinary PhD project that will enable the student to not only conduct theoretical research in Cloud-specific signal and data processing algorithms, but also to apply the theoretical knowledge to solve real-world and industry-specific problems.

Prior experience:

Candidates must have a good first degree in Computer Science, Electrical and Electronic Engineering, Mathematics or closely related subject, and have excellent programming skills in at least one of the programming languages like C++, Python, or MATLAB. Some prior experience on Cloud is highly desirable. Previous experience of carrying out research would be a distinct advantage though it not essential.

Applications should list Dr Jeyan Thiyagalingam as the potential supervisor and choose the option "Department funded PhD" when asked how you will fund the PhD.