Distributed Algorithms CDT
12 Apr 2019
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Funded by EPSRC, the Distributed Algorithms CDT offers studentships at the University of Liverpool with joint supervision from the Hartree Centre.

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At the Hartree Centre, we apply transformative advanced computing, data analytics and AI technologies to industry-relevant challenges, and this is reflected in the projects we're co-supervising with the University of Liverpool as part of the Distributed Algorithms CDT​

Through each of the​​ funded projects below, we hope to provide you with an exciting and engaging area of cutting-edge computational science to immerse yourself in, whilst also delivering essential training in sought-after technical skills that are valued by both science and industry, setting you up for future career success. ​​​​


​​​​​Available projects co-supervised by the Hartree Centre


Faster Uncertainty Quantification of Hydrocodes


Supervisors: 

Prof. Leszek Gasieniec | University of Liverpool

Dr. Luke Mason | STFC Hartree Centre


​The aim of this PhD is to take a specific hydrocode and to examine how these approaches can be used to expedite analysis.  The aim is to develop a single integrated approach to analysing and speeding up UQ on complex systems that is underpinned by a synergistic understanding of computer science and statistics. The anticipation is that this integrated approach would be sufficiently generic and transferable that it could be readily applied to other, similar problems.​

View all available​ projects in the Distributed Algorithms CDT​​  




​Application deadline: 18 April 2022​

​​​​​​​​Meet the supervisors


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Prof. Vassil Alexandrov

I've worked in high performance computing (HPC), data and computational science for a long time, with a fulfilling career spanning 18 years and 5 countries! I've also published over 130 papers in journals and at international conferences and workshops. I'm excited to be a supervisor so that I can pass on my knowledge and experience to the next generation of young people who will develop research projects in exciting areas of HPC and data science.

During my career, I have supervised 31 PhD students to successful completion of their PhD studies across a variety of computational themes and areas, and been a Programme Director of 3 MSc programmes. I am a member of the Editorial Board of the Journal of Computational Science (JOCS) and Editor of Mathematics and Computers in Simulation journal.

My long-term expertise in Monte Carlo means I am particularly interested in seeing how we can further speed up these simulations. Currently, mathematics-led innovation is clearly indispensable in advancing key scientific areas, as well as powering methods and algorithms enabling to discover global properties of data.


Dr. Xiaohu Guo 

I've been interested in science in my whole life, especially computational science, and can see that it is turning into more and more powerful tool for scientists to explore exciting new areas and unknowns. What excites me about computational science is the great sense of achievement I feel when the algorithms/methods that were turned into codes by my logic and own creativity can be used by every one! What I love about working here is bridging a gap between research academics and industrial applications.

I develop enabling technologies for a wide range of engineering and science applications. I was the lead developer of Incompressible Smoothed Particle Hydrodynamics (ISPH) software package ISPH3D which has been recognised the first open source ISPH software package in the world, which has wide application in the area of nuclear thermal hydraulics, offshore and marine energy industries, offshore oil and gas industries and coastal engineering consultancies involved in the design of coastal defences.


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Dr. Jony Castagna

I joined the Science and Technology Facilities Council (STFC) Hartree Centre in 2016 and since then I have enjoyed my work more and more. I am a computational scientist with a strong passion for high performance computing (HPC), usually oriented to the Simulation of Turbulent Flows using Computational Fluid Dynamics… But let me just say it: I love programming GPUs! CUDA is my favourite language, but I recently start to use OpenACC more due its portability to other platforms.  

Working with GPUs since 2010, how could I not end up in Deep Learning? This new fascinating world has recently captured me… and transformed me into an NVIDIA Ambassador here at STFC! So, while I enjoy running NVIDIA Deep Learning Institute courses ranging from CUDA to Deep Learning for Computer Vision, my main focus stays on applied HPC for scientific research, mainly using future computing systems like hybrid CPU-GPU architectures where integration between artificial intelligence (AI) and traditional HPC science is merged together.


Dr. Luke Mason 

I've worked in computational science for 15 years and started by developing control software for embedded and robotic systems before moving to high performance computing (HPC) 10 years ago. I have worked on a diverse range of HPC software over the years, from models of high velocity impact to porting weather and climate models to new computing architectures. I currently lead the High Performance Software Engineering Group at the Science and Technology Facilities Council (STFC) Hartree Centre. We specialise in code scalability and performance on HPC systems, as well as porting and optimisation for emerging technologies and novel architectures.

I enjoy working alongside both industry and academic scientists to produce accurate and efficient code across a range of disciplines and architectures. This Centre for Doctoral Training offers an excellent opportunity to develop new algorithms, optimised for the latest hardware and accelerate their up take into industry.  


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