Grant Funded Researcher

**(Level B) $102,952 to $121,779 per annum plus an employer contribution of up to 17% superannuation applies.**

***Be part of the Australian Institute for Machine Learning - the largest computer vision and machine learning research group in Australia - and contribute to world-leading research projects at the Centre for Augmented Reasoning.**

The postdoctoral researcher for **Multimodal models - metric-based and feature-based membership inference **will be supervised by Associate Professor Qi Wu. This research topic will be explored in collaboration with CSIRO’s Data61 group.

As data exists in different modalities in the real world, viable interactions and combinations among multimodal data feature the creation and discernment of multimodal information in deep learning research. However, pre-trained large multimodal models can often carry more information than single modal models and they are usually applied in sensitive scenarios such as medical report generation and disease identification. Thus, multimodal models may lead to severe data privacy problems. This project studies the data security and privacy issues of large-scale pre-trained multimodal models through the lens of membership inference attack with the aim of determining whether a data record belongs to the training dataset of a model or not.

This postdoctoral role will investigate:
1. The problem of the input and output of the multimodal models being in different modalities, without knowing confidence scores (posterior probabilities) corresponding to the output. This will be examined through the attack methods of:

- metric-based membership inference, utilizing similarity metrics in multimodal models to infer target data membership;
- feature-based membership inference, using a pretrained shadow multimodal feature extractor to discriminate the input and output data.

2. Evaluation of multiple defense mechanisms against attacks.

**This exciting role will contribute to the Centre for Augmented Reasoning’s objective to build world-class research capability in machine learning while demonstrating the potential and impact of this knowledge for industries in Australia.**

**To be successful you will need**:

- A PhD in computer science or related discipline, or equivalent industry experience
- Experience and demonstrable expert knowledge in one or more of the following areas: computer vision, machine learning, and vision and language problems, such as image captioning, visual question answering, and visual dialog
- Strong programming skills, including expertise in relevant languages (e.g. Python, C++) and libraries (e.g. NumPy, PyTorch, TensorFlow)
- Track record of publications in top-tier venues for machine learning, artificial intelligence, computer vision, natural language processing and/or robotics (e.g. NeurIPS, ICLR, CVPR, ICCV, ECCV, PAMI, ICML, JMLR, EMNLP, ACL, ICRA, IROS), commensurate with experience and opportunity
- Fluency in written and spoken English, with an ability to communicate scientific ideas to an expert audience
- Commitment to the principles of equity, diversity and inclusion.

**Desirable characteristics**:

- Has the experience and/or ability to contribute to the promotion of research capabilities to industry and the wider community.

**Enjoy an outstanding career environment**

The Centre for Augmented Reasoning (CAR) is a $20M investment by the (then) Department of Education, Skills and Employment in people and research to make computers better at interacting with humans so that all technology is easier and safer to use. Managed under AIML, the Centre is supporting Advanced Reasoning research through grants and PhD scholarships, facilitating innovation and rapid commercialisation, and increasing artificial intelligence (AI) literacy and engagement in Australia.

The University of Adelaide is a uniquely rewarding workplace. The size, breadth and quality of our education and research programs - including significant industry, government and community collaborations - offers you vast scope and opportunity for a long, fulfilling career.

It also enables us to attract high-calibre people in all facets of our operations, ensuring you will be surrounded by talented colleagues, many world-leading. Our work's cutting-edge nature - not just in your own area, but across virtually the full spectrum of human endeavour - provides a constant source of inspiration.

Our culture is one that welcomes all and embraces diversity consistent with our Staff Values and Behaviour Framework and our Values of integrity, respect, collegiality, excellence and discovery. We firmly believe that our people are our most valuable asset, so we work to grow and diversify the skills, knowledge and capability of all our staff.

We embrace flexibility as a key principle to allow our people to manage the changing demands of work, personal and family life. Flexible working arrangements are on offer for all roles at the University.

In addition, we offer