Research Associate: Deep Variational & Decentralized ML

Macquarie University; Ryde; On-site; AUD 104,000 - 113,000; Full time

Benefits offered by this job

17% Superannuation

Subsidised onsite parking

Flexible working options

Training and professional development

Discounted health insurance (Medibank)

Employee Assistance Program

Sport & Aquatic Centre membership

Job summary

Macquarie University invites a highly skilled research associate to advance foundational work in deep variational and decentralized learning at the AI Lab and Frontier AI Research Centre. You will contribute under the project leader, developing theory, models and publications, while collaborating with a world-class team at North Ryde.

The role requires a Master by Research or higher in AI/data science, strong publication history and ability to coordinate research activities across stakeholders.

Qualifications

• Master by Research or higher in AI, data science or related fields.
• Proven research expertise in statistics, machine/deep learning, information theory, visualization, and data analytics.
• Experience coordinating a research team and assisting research leaders and academic staff.

Responsibilities

• Develop fundamental models for deep variational and decentralized learning.
• Conduct modelling, analytical and visualization tasks.
• Publish findings in top-tier venues and collaborate with project team.

Skills

AI research

Data science

Machine learning

Team coordination

Publications

Analytical thinking

Education

Master by Research or higher

Job description

Macquarie University invites a highly skilled research associate to advance foundational work in deep variational and decentralized learning at the AI Lab and Frontier AI Research Centre. You will contribute under the project leader, developing theory, models and publications, while collaborating with a world-class team at North Ryde.

The role requires a Master by Research or higher in AI/data science, strong publication history and ability to coordinate research activities across stakeholders.