Research Associate/Senior Research Associate in Multimodal Foundation Models

Research Associate/Senior Research Associate in Multimodal Foundation Models Join and apply for the Research Associate/Senior Research Associate in Multimodal Foundation Models role at UNSW. The School of Computer Science and Engineering is offering an opportunity for a Research Associate/Senior Research Associate. In this role, you will conduct both independent and collaborative research within your appointed field and undertake activities to further develop your expertise in deep learning. You will be working on a defence funded project with the research focused on the development of multimodal foundation models using data from a broad range of modalities. The project will develop techniques for pre‑training (such as continual learning and lifelong learning) and post‑training (for example, instruction fine‑tuning and task‑agnostic prompting) that are particularly adapted for robustness across new modalities and tasks, and against adversarial attacks. The models will be evaluated on downstream tasks related to situational understanding and contextual intelligence. This position offers the opportunity to advance your scholarly research and professional activities on both national and international levels. You will contribute to the writing of scientific papers and reports for international journals, participate in conferences and workshops, supervise HDR students, and actively collaborate with industry partners. Location: Kensington – Sydney, AustraliaDue to project timelines candidates must have working rights for Australia. Term and Salary Full time Fixed‑term contract – 3.5 years starting in January 2026 Research Associate (Level A): AUD 113,911 to 121,838 per annum + 17 % superannuation Senior Research Associate (Level B, Step 1): AUD 127,947 per annum + 17 % superannuation Skills and Experience – Level A (Research Associate) A PhD (or soon to be awarded) in a related discipline, and/or relevant work experience. Demonstrated track record in research, evidenced by publications in top‑tier AI and ML conferences such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, with outcomes of high quality and high impact and a clear desire and ability to continuously achieve research excellence and leadership. Strong experience in at least two of the following areas: deep learning and/or computer vision, continual learning, vision‑language models. Experience in developing comprehensive benchmarks. Robust coding and software engineering skills. A strong practice of maintaining open‑source code repositories. Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships. Evidence of highly developed interpersonal skills. An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines. Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training. Skills and Experience – Level B (Senior Research Associate) A PhD in a related discipline, and/or relevant work experience. Demonstrated track record in research, evidenced by publications in top‑tier AI and ML conferences such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, with outcomes of high quality and high impact and a clear desire and ability to continuously achieve research excellence and leadership. Strong experience in all of the following areas: deep learning and/or computer vision, continual learning, vision‑language models. Experience in developing comprehensive benchmarks. Robust coding and software engineering skills. Experience in handling multimodal data, especially videos, is required. Proven commitment to proactively keeping up to date with discipline knowledge and developments. A track record of significant involvement with the profession and/or industry. A strong practice of maintaining open‑source code repositories. High‑level communication skills and ability to network effectively and interact with a diverse range of students and staff. Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships. Evidence of highly developed interpersonal skills. Ability to build effective networks with colleagues. Ability to generate alternative funding and/or industry projects through effective liaison with external local and international researchers, industry and government. An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines. Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training. Contact Eugene Aves – Talent Acquisition ConsultantE: Application Deadline Applications close: 11:55 pm (Sydney time) on Sunday 14 December 2025 EEO Statement UNSW is committed to evolving a culture that embraces equity and supports a diverse and inclusive community where everyone can participate fairly, in a safe and respectful environment. We welcome candidates from all backgrounds and encourage applications from people of diverse gender, sexual orientation, cultural and linguistic backgrounds, Aboriginal and Torres Strait Islander background, people with disability and those with caring and family responsibilities. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment. #J-18808-Ljbffr