Efficient Architectural Designs for Generative AI modelsDescriptionThe Data Science Institute (DSI) at the University of Technology Sydney (UTS) is a world leader in data science and ethical artificial intelligence and has 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 with an aim 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. Leonardo.Ai has also recently been acquired by Canva and now hosts over 200 million users through the combined platforms. Both Leonardo.Ai and Canva have strong principles in: being a good human being foremost, maximizing impact, moving at speed and owning our goals and winning together.
Project Aims This PhD project aims to explore efficient training methods and neural network architectural designs, ranging from increased compression, structured matrices, and methods of reducing parameter 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 as well as delivering 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 e.g. 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, which is located on the waterfront in North Sydney (20 mins train ride from UTS).
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 $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.
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