Research Engineer/Research Fellow in Applied Artificial Intelligence (AI)

Schemes of Service:

Research

Division:

Professional Officers

Employment Type:

Fixed Term

Research Engineer/Research Fellow in Applied Artificial Intelligence (AI)

The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to maximise the potential of its learners and to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society.

SIT is expanding its applied AI research capabilities, building a cohort of academic staff who are keen and experienced working on industry problems /across sectors. Focus areas for applied AI include domains such as:

• Advanced Manufacturing & Semiconductors
• Urban Systems
• AI-Augmented Engineering
• AI Safety & Security
• Chemical Engineering & Biotechnology
• Hospitality and Tourism
• Healthcare

SIT’s Innovation-as-a-Service (IaaS) is an open-innovation platform designed to connect industry players, particularly start-ups and SMEs, with the research and technological capabilities of the Singapore Institute of Technology (SIT), local polytechnics, other IHLS and overseas university partners.

IaaS Centre of Digital Innovation focusses on assisting company’s to digitalize their operations or products and implementing AI solutions using ready AI tools to ensure a fast implementation to market.

Key Responsibilities

• Work closely with centre head, Principal Investigator (PI) and internal/external stakeholders (including other IHLs) to support or drive applied research, and innovation initiatives outcomes.
• Outcomes include impact or revenue of industry partners
• Understand industry partners requirements and help create proposals to them.
• Work with the team to create IP (Intellectual Property) from internal grants to target multiple adopters

Job Requirements:

• A good Bachelor’s degree or Master’s degree in Computer Science, Engineering, or a related discipline, with demonstrated experience in Artificial Intelligence (AI) / Machine Learning (ML) research or application.
• Strong technical expertise in one or more of the following areas: Computer Vision and Image Processing, Machine Learning, Deep Learning, and Reinforcement Learning, Large Language Models (LLMs) and Multimodal Models, Generative AI, Agentic AI, Physical AI, and Embodied AI, Trustworthy AI, including explainability, auditability, and privacy, Edge AI and model optimisation, Physics-informed neural networks (PINNs) and surrogate modelling, Time-series modelling and anomaly detection, Bayesian methods and uncertainty quantification, Graph Neural Networks (GNNs), Spatiotemporal data engineering, Digital twins and simulation, Demonstrated Applied AI for Healthcare and clinical practice, Industry 4.0 and/or Industry 5.0 (added advantage)
• Experience applying AI to one or more of SIT’s focus areas: Advanced Manufacturing & Semiconductors, Urban Systems, AI-Augmented Engineering, AI Safety & Security, Chemical Engineering & Biotechnology, AI for Healthcare as well as Hospitality & Tourism.
• Deep technical specialist with 8 or more years of working experience as a Machine Learning Engineer or similar role, with good knowledge of industry practices and technological applications in the field for the senior positions. 1 - 3 years experience will suffice for research engineers.
• Must have a firm grasp and understanding of data structures, data modeling and software architecture using Python, R, Java and C/C#/C++, as well as competence in mathematics including probability, statistics and algorithms.
• Keen interest to support research and academic project work, with demonstrated ability in developing software solutions to technical problems.
• Demonstrate proficiency to keep abreast of developments in the field and pursue professional certification programs.

Key Competencies

• Self-motivated and can work independently or in a team.
• Enjoy both analytical and hands-on work to solve problems.
• Able to build and maintain good working relationships with people within and external to the university.
• Flexibility to work across functions/teams as part of a team in a dynamic environment.
• Self-directed learner who believes in continuous learning and development
• Proficient in technical writing and presentation
• Possess good analytical and critical thinking skills
• Shows good initiative and takes ownership of work undertaken
• Proactive, resourceful, and able to take ownership of assigned responsibilities