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Flora Salim

Professor

University of New South Wales
Country flagAustralia

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Positions (1)

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Flora Salim

University Name
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University of New South Wales

UNSW School of Computer Science and Engineering is advertising multiple academic openings across computing and AI-related areas, including Cybersecurity , Cryptography , Machine Learning , Natural Language Processing , Neurosymbolic AI , Software Engineering , and Systems . The post highlights 12 positions in total, spanning Associate Professor, Lecturer, and Senior Lecturer roles, with both education-focused and teaching-and-research opportunities. The linked job advert shown here is for a Lecturer/Senior Lecturer (Education Focussed) in Cybersecurity at the University of New South Wales in Sydney, Australia. The role involves teaching and curriculum development in cybersecurity topics such as penetration testing, reverse engineering, wargaming, offensive and defensive security, and related undergraduate/postgraduate teaching. UNSW emphasizes its strong environment in computer science, cybersecurity, systems, AI, and software engineering. Eligibility highlights: Lecturer (Level B) applicants should have a PhD in a related discipline and/or relevant work experience, plus teaching experience and evidence of teaching effectiveness. Senior Lecturer (Level C) applicants should also have a PhD and/or relevant experience, with stronger evidence of educational leadership, curriculum innovation, mentoring, and contribution to teaching excellence. Applicants should be able to support diverse student cohorts and demonstrate commitment to equity, diversity, inclusion, and health and safety. Funding / employment terms: This is a paid academic appointment, not a scholarship. The advertised salary for Lecturer (Level B) is AUD $127,947–$150,830 per annum plus 17% superannuation, and for Senior Lecturer (Level C) AUD $155,403–$178,290 per annum plus 17% superannuation. The role is described as a full-time 2-year convertible tenure track or continuing appointment. Application window: Applications close on 31 July 2026 (Sydney time). Applicants should apply through the UNSW careers portal, upload a CV and cover letter, and address the Skills and Experience criteria. The post also notes that a ROPE statement may be included if relevant.

2 months ago

Articles (14)

The spread of infectious diseases is a highly complex spatiotemporal process, difficult to understand, predict, and effectively respond to. Machine learning and artificial intelligence (AI) have achieved impressive results in other learning and prediction tasks; however, while many AI solutions are developed for disease prediction, only a few of them are adopted by decision-makers to support policy interventions. Among several issues preventing their uptake, AI methods are known to amplify the bias in the data they are trained on. This is especially problematic for infectious disease models that typically leverage large, open, and inherently biased spatiotemporal data. These biases may propagate through the modeling pipeline to decision-making, resulting in inequitable policy interventions. Therefore, there is a need to gain an understanding of how the AI disease modeling pipeline can mitigate biased input data, in-processing models, and biased outputs. Specifically, our vision is to develop a large-scale micro-simulation of individuals from which human mobility, population, and disease ground truth data can be obtained. From this complete dataset – which may not reflect the real world – we can sample and inject different types of bias. By using the sampled data in which bias is known (as it is given as the simulation parameter), we can explore how existing solutions for fairness in AI can mitigate and correct these biases and investigate novel AI fairness solutions. Achieving this vision would result in improved trust in such models for informing fair and equitable policy interventions.

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2024

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2021

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2020

Collaborators (18)

Luca Bedogni

Associate Professor

University of Modena and Reggio Emilia

ITALY
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Azadeh Ghari Neiat

Deakin University

AUSTRALIA
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Klaus David

University of Kassel

GERMANY
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Aaqib Saeed

Eindhoven University of Technology

NETHERLANDS
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Allison Kealy

Professor

RMIT University

AUSTRALIA
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Athman Bouguettaya

University of Sydney

AUSTRALIA
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Li Xiong

Professor

Emory University

UNITED STATES
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C. Raina MacIntyre

University of New South Wales

AUSTRALIA
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Matthew Scotch

Professor

Arizona State University

UNITED STATES
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Sandra Ohly

Professor and group leader

University of Kassel

GERMANY
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Matt Duckham

RMIT University

AUSTRALIA
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Andreas Züfle

Emory University

UNITED STATES
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Jelena Gabela

TU Wien

AUSTRIA
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Jeffrey Chan

Associate Professor

RMIT University

AUSTRALIA
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Du Yong Kim

Curtin University

AUSTRALIA
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Yaguang Tao

RMIT University

AUSTRALIA
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JIANZHONG QI

University of Melbourne

AUSTRALIA
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Mohammad Saiedur Rahaman

RMIT University

AUSTRALIA
View details
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