Full Time Faculty, Research Track Positions at the Associate or Full Professor Levels in Learning Science, Technologies and Andragogy, SMU Resilient Workforces Institute (ResWORK)

The Resilient Workforces Institute (ResWORK) at Singapore Management University (SMU) invites applications for a full-time, non-tenurable Research Track faculty position, ideally at the Associate or Full Professor level in the area of Learning Science, Technologies and Andragogy. This is a fixed-term appointment for three years in the first instance, with the possibility of renewal.

Research Track faculty at SMU are expected to pursue high-quality, impactful research, contribute to interdisciplinary scholarship, secure grant funding and participate in the broader academic and intellectual thrusts of ResWORK and SMU. The teaching load is pegged to be lower than that of equivalent tenure-track faculty and is nominally a single course per year. Applicants are evaluated primarily in terms of research credentials and successful candidates can expect to have clear KPIs primarily in terms of high-quality research publications, competitive grant success and research impact.

ResWORK is a university-level research institute dedicated to advancing research on the future of work and lifelong learning, with a goal of building resilient workforces through interdisciplinary research. Its research agenda focuses on how technological, organisational and societal changes are transforming the nature of work, adult learning and employment, and how individuals, organisations and societies can adapt to these changes.

The Institute's first research pillar, Optimising Human-Machine Collaboration, focuses on understanding and designing effective interactions between individual humans and intelligent machines, including AI agents and robotic systems, to enable successful learning (including reskilling and upskilling of mature workers) and execution of professional tasks.

We are particularly interested in candidates who can strengthen ResWORK's research capability in AI-enhanced adult learning, especially through the application of Science-of-Learning (SoL) principles to innovations in andragogical practice and the design of AI agents that adapt to the socio-cognitive contexts of individual learners

Candidates may work on areas such as, but are not limited to:

· AI agents for learning and education

· Learning science and the design of intelligent learning systems

· Human-AI interaction in learning environments

· AI-supported learning, teaching and training for both cognitive and physical skills

· Cognitive science and learning technologies

· Adaptive and personalised learning systems

· Design and evaluation of AI agents informed by Science-of-Learning principles

· Learning analytics and AI-enabled learning interventions

· Human-AI collaboration in education and workplace learning

We welcome applicants trained in Learning Sciences, Educational Technology, Cognitive Science, Computer Science, Artificial Intelligence, Human-Computer Interaction, Education, Psychology, or cognate disciplinary or interdisciplinary fields with a strong focus on learning and intelligent technologies, especially as applied to adult learners.

Candidates who can demonstrate bold interdisciplinarity aspirations and a strong research agenda at the intersection of AI, learning and human development are particularly encouraged to apply.

Applicants should be able to:

· Conceptualise and execute high-quality, internationally-competitive research projects on AI, learning and human-machine collaboration

· Develop competitive grant applications and secure external research funding

· Publish high-quality research in leading international journals and/or conferences

· Develop and lead interdisciplinary research programmes aligned with ResWORK's research priorities, spanning the future of work, lifelong learning and human-machine collaboration

· Design and deliver undergraduate, postgraduate or executive education courses in relevant areas

· Forge productive collaborations with researchers, industry partners, government agencies and other stakeholders

· Contribute to the broader intellectual life of ResWORK and SMU

The Resilient Workforces Institute (ResWORK) at Singapore Management University (SMU) invites applications for a full-time, non-tenurable Research Track faculty position, ideally at the Associate or Full Professor level in the area of Learning Science, Technologies and Andragogy. This is a fixed-term appointment for three years in the first instance, with the possibility of renewal.

Research Track faculty at SMU are expected to pursue high-quality, impactful research, contribute to interdisciplinary scholarship, secure grant funding and participate in the broader academic and intellectual thrusts of ResWORK and SMU. The teaching load is pegged to be lower than that of equivalent tenure-track faculty and is nominally a single course per year. Applicants are evaluated primarily in terms of research credentials and successful candidates can expect to have clear KPIs primarily in terms of high-quality research publications, competitive grant success and research impact.

ResWORK is a university-level research institute dedicated to advancing research on the future of work and lifelong learning, with a goal of building resilient workforces through interdisciplinary research. Its research agenda focuses on how technological, organisational and societal changes are transforming the nature of work, adult learning and employment, and how individuals, organisations and societies can adapt to these changes.

The Institute's first research pillar, Optimising Human-Machine Collaboration, focuses on understanding and designing effective interactions between individual humans and intelligent machines, including AI agents and robotic systems, to enable successful learning (including reskilling and upskilling of mature workers) and execution of professional tasks.

We are particularly interested in candidates who can strengthen ResWORK's research capability in AI-enhanced adult learning, especially through the application of Science-of-Learning (SoL) principles to innovations in andragogical practice and the design of AI agents that adapt to the socio-cognitive contexts of individual learners

Candidates may work on areas such as, but are not limited to:

· AI agents for learning and education

· Learning science and the design of intelligent learning systems

· Human-AI interaction in learning environments

· AI-supported learning, teaching and training for both cognitive and physical skills

· Cognitive science and learning technologies

· Adaptive and personalised learning systems

· Design and evaluation of AI agents informed by Science-of-Learning principles

· Learning analytics and AI-enabled learning interventions

· Human-AI collaboration in education and workplace learning

We welcome applicants trained in Learning Sciences, Educational Technology, Cognitive Science, Computer Science, Artificial Intelligence, Human-Computer Interaction, Education, Psychology, or cognate disciplinary or interdisciplinary fields with a strong focus on learning and intelligent technologies, especially as applied to adult learners.

Candidates who can demonstrate bold interdisciplinarity aspirations and a strong research agenda at the intersection of AI, learning and human development are particularly