The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry‑relevant degree programmes that prepare graduates to be work‑ and future‑ready professionals. SIT’s mission is to maximise the potential of its learners and to innovate with industry through an integrated applied learning and research approach. Our distinctive pedagogy integrates work and study, emphasising authentic, real‑world learning through close collaborations with strategic industry partners. SIT’s centralised campus in the Punggol Digital District, together with strategically deployed “Living Labs,” provides a tightly integrated ecosystem where academia, industry, and community converge.

SIT is expanding its applied AI research capabilities, building a cohort of AI faculty who are keen and experienced working on industry problems across sectors. We are recruiting faculty candidates at all levels of seniority.

Responsibilities:

• Lead and contribute to applied research projects with industry partners and government agencies in one or more of the following AI application areas:
  • Advanced Manufacturing & Semiconductors
  • Urban Systems
  • AI-Augmented Engineering
  • AI Safety & Security
  • Chemical Engineering & Biotechnology
  • Healthcare
  • Hospitality & Tourism
• Develop and teach applied AI courses within the cluster’s programmes and across relevant interdisciplinary modules.
• Supervise Industry Doctorate/Masters and capstone projects in collaboration with domain faculty and industry partners.
• Contribute to SIT’s continuing education offerings.
• Serve as AI mentor for existing SIT domain faculty through joint projects and co-supervision mechanisms.

Qualifications:

• PhD in Computer Science, Engineering, or a relevant domain with demonstrated AI/ML research experience. Equivalent industry experience may also be considered.
• Technical expertise and deep knowledge of one or more of the following areas:
  • Physics-informed neural networks (PINNs) & surrogate modelling
  • Time-series modelling & anomaly detection
  • Bayesian methods & uncertainty quantification
  • LLMs & multi-modal models
  • Graph neural networks (GNNs)
  • Reinforcement learning
  • Edge AI & model optimisation
  • Trustworthy AI (explainability, auditability, privacy)
  • Spatiotemporal data engineering
  • Digital twins & simulation
• Experience applying AI to the SIT’s focus areas
• Demonstrated leadership and evidence of working on industry/society-defined problems
• Experience with industry research collaborations, applied research grants, and/or system deployment
• Established thought leadership and/or professional standing e.g. publications in top journals and keynotes
• Non-publication outputs and impact such as open-source tools, technical reports, patents, deployed systems
• Track record of cross-disciplinary collaborations
• Strong supervisory and mentoring skills, with an interest in working closely with students in an educational environment.

• Ability to communicate clearly with domain experts, industry practitioners and the general public

What SIT offers:

• An applied research environment to tackle real-world problems together with industry partners
• Opportunities to shape a coherent applied AI research agenda with colleagues across disciplines and build Singapore’s applied AI research capability at a pivotal moment
• Access to SIT’s Living Lab Network and Punggol Digital District ecosystem as testbeds
• SIT values applied research impact and evaluates faculty according to how their research makes a difference to society or industry
• Singapore’s exceptional quality of life, competitive personal tax environment, and position as Asia’s leading research and innovation hub

How to apply:

Candidates should submit the following:

• Curriculum vitae including grants, publications, and non-publication outputs (code, datasets, patents, technical disclosures)
• Cover Letter
• Research statement (up to 3 pages) addressing your applied AI research programme, how it connects to SIT’s cluster context, and your experience with industry-connected research. Highlight three past research outputs with a brief explanation of each output’s impact.
• Teaching statement (up to 1 page) addressing your approach to applied learning