Efficient Architectural Designs for Generative AI models
Description The Data Science Institute (DSI) at the University of Technology Sydney (UTS) is a world leader in data science and ethical artificial intelligence, with a strong focus on industry engagement. The DSI boasts over 200 PhD students and 100 academic staff with award-winning researchers in AI.
In collaboration with Leonardo.Ai, we are advertising an industry PhD program that will tackle research questions at the bleeding edge of GenAI research, aiming to drive forward both foundational research in the field through traditional publication outputs, as well as supercharging the Leonardo.Ai platform. Leonardo.Ai is a world leader in generative AI and is building one of the leading AI laboratories in foundational AI research. Recently acquired by Canva, it now hosts over 200 million users through the combined platforms, with strong principles of being a good human being, maximizing impact, moving at speed, owning our goals, and winning together.
Project Aims This PhD project aims to explore efficient training methods and neural network architectural designs, focusing on increased compression, structured matrices, and methods of reducing parameters and/or computation without compromising performance. The student will conduct foundational research exploring these methods and push the envelope of the performance of our current suite of multi-modal models. We expect the student to publish in these areas and deliver significant enhancements to our product.
PhD research students will have access to leading-edge compute facilities (e.g., H100s), a team of world-class research leaders across both UTS, Leonardo, and Canva, cutting-edge datasets to conduct research, and mentoring and guidance to complete a best-in-class PhD research program.
Eligibility We are looking for the best of the best! You will be adequately qualified to enter the UTS PhD scheme with Undergraduate/Postgraduate Qualifications in Computer Science, Data Science, AI, Physics, Mathematics, or equivalent.
Candidate Profile A strong background in programming, mathematics, statistics, or related areas.Knowledge and interest in Diffusion, GANs, LLMs, and generative AI in general as demonstrated by independent project work in GitHub.Proficiency in modern deep learning frameworks such as Pytorch or Jax.Ideally, we are looking for candidates with previous experience in top-tier Tech companies. We, however, welcome applications from underrepresented groups and diverse backgrounds.Proficiency in English (both verbal and written).Location This PhD will be hosted at the University of Technology Sydney, and the student will spend significant time at the Leonardo.Ai headquarters, located on the waterfront in North Sydney (20 mins train ride from UTS).
Scholarship Information Full Domestic Scholarship: Open to Australian citizens who will receive a full scholarship of $37k per year stipend + $10k per year top-up for 3.5 years.
Full International Scholarship: Open to all international applicants with a $37k per year stipend, $45k per year international fees, and $30k per year top-up for 3.5 years. Student visas will be provided by UTS.
#J-18808-Ljbffr