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PhD scholarships and computing resources to accelerate AI-enabled research success for our next generation 

Program Information

HPC-AI has now become a bundled term due to the rapid progress of deep learning architectures, which are empowered by running AI applications at scale on supercomputing infrastructures. NCI empowers a wide range of research that needs computing, storage, and cloud resources through various merit-based allocation schemes.  However, most PhD students are not eligible as independent lead CI to apply for the national scheme. To address the growing demand for computing and storage resources of the HPC-AI application, as well as supporting our next generation of researchers, NCI offers 100KSU with appropriate storage and AUD$10,000 per year for each successful application for eligible PhD project costs to support PhD programs through the NCI Australia HPC-AI Talent Program.

NCI supports AI applications on diverse scientific problems such as solving differential equations, accelerating molecular dynamics, predicting 3-dimensional protein structures, controlling nuclear fusion, or weather forecasting with higher resolution and accuracy. Some HPC-AI applications encounter a range of workflow bottlenecks. The performance can be limited by processes that are compute bound, I/O bound, memory bound, or a combination of the above, pushing the need for HPCD into the exascale range. The unprecedented representational ability of deep neural network structures can only be brought to bear on the most complex and urgent global problems by model training with ultra-large datasets on heterogeneous exascale HPCD architectures. Through this program, we will identify implementation hurdles and barriers, provide support to address them for the next generation of young researchers who in turn will empower their future organisations for the broader benefit of the Australian research and industry sectors. 

Value

$10,000 and 100KSU with appropriate storage per annum  2023

Eligibility

NCI will support up to 10 PhD students for 1-year supplements to their PhD program in 2023. Additional project funds and compute resources should be used within the year of the award.  

NCI intends to run the program again in 2024 and beyond. Only one award will be made per individual, as it is expected that participants will become competitive in NCI’s merit allocation schemes (particularly NCI Adapter, or joining a supervisor’s application to NCMAS) following the award. 

Eligibility: 

  • Enrolling full-time in a program of study for the degree of Doctor of Philosophy, including:
    • First year PhD students in the year of application. 
    • Final year PhD students, subject to the finishing timeline of their PhD program.
  • Students enrolled in PhD programs at recognised Australian and New Zealand universities only. 
  • All research fields that apply HPC and/or AI techniques.

Enquiries 

Should you have any questions, please direct them to training.nci@anu.edu.au. 

Application Process

Eligible candidates must apply through the application process outlined below for the scholarship program.  Incomplete applications will not be considered. 

Selection is merit-based by an independent Assessment Committee. The Assessment Committee’s decision is final and cannot be appealed.  

DateSteps
20 Dec 2022 Applications open
31 Jan 2023Applications close
1 – 22 Feb 2023Assessment Committee review and decision 
Extended 23 Feb 2023Scholarship result announcement


Application Submission

Please provide your resume (2 pages maximum), two reference letters (each 1-page maximum) and your application (2 pages maximum) to training.nci@anu.edu.au as PDF attachments. Please use the Application Template file below. 

studentship_application_NAME_ORG.docx

Program stages

For successful scholarship recipients, program reviews are conducted each quarter for the duration of the program and a final report is required at the end of the program.  

DateStages
Feb 2023

Onboarding with NCI training

Mar 2023

Project plan initial review 

May 2023Quarter 1 review 
Aug 2023Quarter 2 review and mid-term showcase 
Nov 2023

Quarter 3 review

Jan 2024 Final report
Feb 2024 End of program presentation and symposium


More details to be released. Subscribe to the NCI newsletter to stay up to date.


Successful Applicants

Tanvir Saurav

Tanvir Saurav is a PhD student in the Bushfire Research Group, School of Science, UNSW Canberra.

He was born and raised in Bangladesh. After high school, he moved to the US where he completed a B.S. in Mechanical Engineering from Temple University in 2018 and joined the Master of Philosophy (M.Phil.) program at The University of Melbourne where he worked on direct numerical simulation of rough-wall turbulent flows using high-performance computing. 

He joined the PhD program at UNSW Canberra in 2022. His current research areas are turbulence, computational fluid dynamics, and high-performance computing. He uses numerical methods and supercomputers to model and simulate ember transport in bushfires.

Ke Ding

Ke Ding is a PhD student from the Wen Group at the John Curtin School of Medical Research. Ke's research projects focus on building DL models to uncover the interaction among RNA binding proteins and summarise transcription factor binding sites' characteristics, and he has been using Gadi's GPU nodes to train deep neural networks. In addition, since the size of genomic data is enormous, he has been using Gadi's CPU nodes to process the big data.


Brenda Almirall


Hannah Kessenich


Tong Xie


Zachary Cooper-Baldock