Total 21 construction quality control job vacancies in Education / Training category

School of Electrical and Electronic Engineering is one of the founding Schools of the Nanyang Technological University. Built on a culture of excellence, the School is renowned for its high academic standards and research. With over 3,000 undergraduates students and 2,000 graduate students it is one of the largest EEE schools in the world and ranks 4th in the field of Electrical & Electronic Engineering in the 2025 QS World University Rankings by Subjects.

Today, the School has become one of the world’s largest engineering schools that nurtures competent engineers and researchers. Each year, the School graduates over a thousand students who are ready to take on great ambitions and challenges.

For more details, please view: https://www.ntu.edu.sg/eee

We are looking for research assistants to conduct research in the areas of safety-critical control theory and machine learning. The role will focus on combining new theory or method in nonlinear system control and state-of-the-art machine learning systems, with applications to various robotic systems.

Key Responsibilities:

• Conduct research in the area of control theory and machine learning

• Conduct experiments on different robotic platforms

• International collaborations in the above areas

• Publish papers in related top journals and conferences

Job Requirements:

• Bachelor’s degree in control theory, machine learning, robotics, or related field

• Familiarity with nonlinear systems and control theory/state-of-the-art machine learning systems (diffusion, transformers, etc.)/robotics.

• Good written and oral communication skills

• Proficiency in programing (e.g., Python) and machine learning tools (e.g., PyTorch)

• Entry level candidates are welcome to apply

We regret to inform you that only shortlisted candidates will be notified.

We are hiring a Training and Quality Assurance Manager to lead staff capability development, service quality standards and continuous improvement across our wellness and traditional therapy outlets in Singapore.

Key Responsibilities:

- Design, implement and review training programmes for service staff, outlet teams and supervisors.

- Develop training materials, SOP guides and service quality benchmarks to support operational consistency.

- Conduct staff assessments, coaching sessions and refresher training to improve service performance.

- Monitor customer feedback, service quality indicators and operational compliance standards.

- Perform outlet audits and identify areas for improvement in service execution and customer experience.

- Work closely with management and outlet leaders to strengthen service quality, team discipline and customer satisfaction.

- Support onboarding and structured skills development for new employees.

- Prepare training reports, quality review findings and improvement recommendations for management.

Requirements:

- Strong ability to develop SOPs, training systems and quality monitoring processes.

- Good leadership, coaching and communication skills.

- Strong organisational skills and attention to detail.

- Experience in service, hospitality, healthcare, wellness or retail operations will be an advantage.

- Ability to support a multi-outlet environment and continuous improvement initiatives.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Construction-Robotics%29/32520-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) is seeking to recruit a Research Fellow (RF) to participate in innovative general research focused on robotics and automation within the construction and built environment. 

The successful candidate will play a key role in developing an algorithmic solution for robotics that integrated with Building Information Modeling (BIM). Key responsibilities include designing the software architecture, applying advanced robotics techniques to support project objectives, collaborating closely with multidisciplinary teams, and leading groups of student interns. In addition to project-specific research tasks, the Research Fellow will be expected to handle administrative and operational matters related to the Centre for Construction Robotics & Automation (CCRA). 

Job Requirements

•    At least a PhD in Mechanical Engineering with a specialization in Robotics, or related field from a reputable university.
•    Evidence of strong publication record in top academic journals.
•    Proficiency in programming languages, particularly in Python or Matlab for automation and data analysis tasks.
•    Prior Civil Engineering/Built Environment related experience, practices and workflows will be an added advantage.  
•    Strong research experience, specifically in past research projects related to robotics or scene graphs is required.
•    Strong written and oral communication skills.
•    Open to fixed-term contract.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28LLM-for-Construction-Safety%29/32519-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) is seeking a highly motivated and talented Research Engineer to join a groundbreaking, government-funded research project: MIDAS. This project aims to transform Design for Safety (DfS) in the construction and built environment sectors by developing an advanced, AI-driven advisory platform. MIDAS will leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multimodal data (text, images, and Building Information Models) to proactively identify design risks and recommend mitigation measures throughout a project's lifecycle. 

The successful candidate will play a pivotal role in assisting with the core technical development of the MIDAS platform, specifically focusing on multimodal data ingestion and the RAG-based LLM reasoning engine. Key responsibilities include designing the algorithms, collaborating closely with multidisciplinary teams, and leading groups of student interns. 

Job Requirements

•    At least a bachelor’s in Civil Engineering, Built Environment, Computer Science or related field from a reputable university. Masters will be preferred.
•    Evidence of strong publication record in top academic journals
•    Proficiency in programming languages, particularly in Python or Matlab for automation and data analysis tasks
•    Familiarity working with Large Language Models and building RAG architectures.
•    Familiarity with BIM, IFC and graph databases.
•    Strong research experience, specifically in past research projects related to robotics or scene graphs is required
•    Strong written and oral communication skills.
•    Open to fixed-term contract

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28LLM-for-Construction-Safety%29/32518-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) is seeking a highly motivated and talented Research Fellow (RF) to join a groundbreaking, government-funded research project: MIDAS. This project aims to transform Design for Safety (DfS) in the construction and built environment sectors by developing an advanced, AI-driven advisory platform. MIDAS will leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multimodal data (text, images, and Building Information Models) to proactively identify design risks and recommend mitigation measures throughout a project's lifecycle. 

The successful candidate will play a pivotal role in driving the core technical development of the MIDAS platform, specifically focusing on multimodal data ingestion and the RAG-based LLM reasoning engine. Key responsibilities include designing the algorithms, collaborating closely with multidisciplinary teams, and leading groups of student interns. 

Job Requirements

•    At least a PhD in Civil Engineering, Built Environment, Computer Science or related field from a reputable university.
•    Evidence of strong publication record in top academic journals. 
•    Proficiency in programming languages, particularly in Python or Matlab for automation and data analysis tasks
•    Proven experience working with Large Language Models and building RAG architectures.
•    Familiarity with BIM, IFC and graph databases.
•    Familiarity with Computer Vision techniques.
•    Strong research experience, specifically in past research projects related to robotics or scenegraphs is required
•    Strong written and oral communication skills.
•    Open to fixed term contract. 

We are seeking a highly motivated candidatewho has strong experience in auditing IFRS financial statements, as well as apassion for learning and knowledge, to join us as Learning and DevelopmentManager for the Audit and Assurance division.  You will play a pivotalrole in enhancing the skills, knowledge, and performance of our employeesprimarily in the Audit & Assurance businesses, ensuring the continuousdevelopment and success of our workforce.

Responsibilities

• Work closely with key stakeholders on training needs to drive continuous improvements to the existing learning ecosystem.
• Design, develop and implement training and development programs that are aligned with the Firm’s strategy and address skill gaps within the workforce.
• Design, develop and deliver trainings related to financial reporting and audit methodology to the Audit and Assurance professional practice.
• Manage and monitor the deployment of training courses, including onboarding trainings for new employees.
• Ensure that the training programs and talent management practices comply with relevant regulations and standards.
• Prepare information required for external and in-house monitoring / compliance checks on training-related matters.
• Identification of training needs through participation in the Firm’s internal quality review processes.
• Provide coaching to Learning & Development support staff.

The successful candidate should have thefollowing skills and experience:

• Degree or equivalent qualification in Accounting and Finance,
• Strong audit and accounting background supported by at least 6 years of experience in conducting audits of financial statements.
• Experience in content development and delivery of Audit and Assurance trainings with excellent presentation/facilitation skills and ability.
• Proficient in Microsoft Office, and familiar with virtual delivery platforms including Microsoft Teams and Zoom.  Prior experience with learning management systems is preferred.
• Meticulous with strong organisation and administration skills.

Job Descriptions:

• Support the Workplace Safety and Health Officer (WSHO) in implementing, monitoring, and enforcing the Workplace Safety and Health Management System (WSHMS) in compliance with statutory requirements, LTA safety standards, and project specifications.
• Assist in the administration, control, and verification of the Permit-To-Work (PTW) system, ensuring all works are properly risk assessed and authorised prior to commencement.
• Conduct regular site safety inspections, surveillance, and compliance audits to ensure adherence to WSH Act, subsidiary legislations, LTA safety procedures, and company safety policies.
• Monitor high-risk construction activities and ensure effective implementation of Risk Assessments (RA), Safe Work Procedures (SWP), Method Statements, and control measures.
• Assist the WSHO in accident/incident investigations, including evidence collection, root cause analysis, corrective actions, and submission of investigation reports.
• Maintain proper documentation and records of safety training, inspections, incident statistics, safety certifications, competency records, and regulatory submissions.
• Verify and maintain updated records of workers’ trade certifications, safety passes, and statutory competency requirements prior to site deployment.
• Conduct Safety Induction Courses (SIC), refresher briefings, toolbox meetings, and safety awareness programmes in accordance with LTA and project requirements.
• Perform duties as a WSH Trainer by planning, delivering, and evaluating WSH training programmes to enhance safety competency and promote positive safety culture across all workforce levels.
• Develop, review, and update safety training materials, presentations, and learning resources aligned with regulatory requirements and project risk profiles.
• Provide coaching and on-site guidance to supervisors, workers, subcontractors, and suppliers on safe work practices and hazard prevention measures.
• Monitor environmental and weather conditions including WBGT, lightning alerts, air quality, UV index, rainfall, and wind conditions, and promptly communicate work restrictions or safety advisories.
• Support implementation of Hazard Identification, Risk Assessment and Risk Control (HIRARC) processes and continuous improvement initiatives.
• Monitor usage, inspection, and adequacy of Personal Protective Equipment (PPE) and safety equipment to ensure compliance.
• Prepare safety statistics, reports, presentation materials, and documentation for Safety Committee Meetings, Management Reviews, and LTA audits.
• Attend coordination meetings, WSH committee meetings, subcontractor meetings, daily toolbox meetings, and pre-start briefings to address safety matters.
• Liaise and coordinate with subcontractors, suppliers, and stakeholders to ensure compliance with project safety requirements and contractual obligations.
• Ensure safety signage, barricades, warning systems, and safety communication materials are properly installed, visible, and maintained throughout the worksite.
• Participate in emergency preparedness planning, drills, and crisis response exercises; ensure all personnel are aware of emergency procedures and evacuation arrangements.
• Escort injured persons to medical facilities and assist in incident reporting and follow-up actions.
• Conduct site safety assessments prior to endorsement or recommendation for PTW approvals.
• Support preparation for regulatory inspections, internal audits, and LTA safety inspections, ensuring readiness and compliance at all times.
• Perform all duties in accordance with Workplace Safety and Health Act, Environmental Protection regulations, LTA requirements, and project contractual safety obligations.
• Carry out any additional safety-related duties as assigned by the WSHO, Project Manager, or Project Director.

Job Requirements:

• Diploma or Degree in Workplace Safety & Health, Engineering, Construction Management, Environmental Management, or related discipline.
• Valid WSH Coordinator Certificate recognised by MOM, Singapore.
• Experience in conducting safety training programmes.
• Minimum 5 years of WSH experience in construction projects.
• Experience in MRT / LTA / infrastructure projects will be an advantage.
• Familiar with WSH Act, subsidiary legislations, PTW system, RA & SWP implementation.
• Environmental Control Officer (ECO) certification will be an added advantage.
• Good communication and interpersonal skills with ability to engage site workforce and subcontractors.
• Able to work independently in a fast-paced construction environment.
• Willing to work at construction site and perform night shift / shift work when required.

Job Descriptions:

• Support the Workplace Safety and Health Officer (WSHO) in implementing, monitoring, and enforcing the Workplace Safety and Health Management System (WSHMS) in compliance with statutory requirements, LTA safety standards, and project specifications.
• Assist in the administration, control, and verification of the Permit-To-Work (PTW) system, ensuring all works are properly risk assessed and authorised prior to commencement.
• Conduct regular site safety inspections, surveillance, and compliance audits to ensure adherence to WSH Act, subsidiary legislations, LTA safety procedures, and company safety policies.
• Monitor high-risk construction activities and ensure effective implementation of Risk Assessments (RA), Safe Work Procedures (SWP), Method Statements, and control measures.
• Assist the WSHO in accident/incident investigations, including evidence collection, root cause analysis, corrective actions, and submission of investigation reports.
• Maintain proper documentation and records of safety training, inspections, incident statistics, safety certifications, competency records, and regulatory submissions.
• Verify and maintain updated records of workers’ trade certifications, safety passes, and statutory competency requirements prior to site deployment.
• Conduct Safety Induction Courses (SIC), refresher briefings, toolbox meetings, and safety awareness programmes in accordance with LTA and project requirements.
• Perform duties as a WSH Trainer by planning, delivering, and evaluating WSH training programmes to enhance safety competency and promote positive safety culture across all workforce levels.
• Develop, review, and update safety training materials, presentations, and learning resources aligned with regulatory requirements and project risk profiles.
• Provide coaching and on-site guidance to supervisors, workers, subcontractors, and suppliers on safe work practices and hazard prevention measures.
• Monitor environmental and weather conditions including WBGT, lightning alerts, air quality, UV index, rainfall, and wind conditions, and promptly communicate work restrictions or safety advisories.
• Support implementation of Hazard Identification, Risk Assessment and Risk Control (HIRARC) processes and continuous improvement initiatives.
• Monitor usage, inspection, and adequacy of Personal Protective Equipment (PPE) and safety equipment to ensure compliance.
• Prepare safety statistics, reports, presentation materials, and documentation for Safety Committee Meetings, Management Reviews, and LTA audits.
• Attend coordination meetings, WSH committee meetings, subcontractor meetings, daily toolbox meetings, and pre-start briefings to address safety matters.
• Liaise and coordinate with subcontractors, suppliers, and stakeholders to ensure compliance with project safety requirements and contractual obligations.
• Ensure safety signage, barricades, warning systems, and safety communication materials are properly installed, visible, and maintained throughout the worksite.
• Participate in emergency preparedness planning, drills, and crisis response exercises; ensure all personnel are aware of emergency procedures and evacuation arrangements.
• Escort injured persons to medical facilities and assist in incident reporting and follow-up actions.
• Conduct site safety assessments prior to endorsement or recommendation for PTW approvals.
• Support preparation for regulatory inspections, internal audits, and LTA safety inspections, ensuring readiness and compliance at all times.
• Perform all duties in accordance with Workplace Safety and Health Act, Environmental Protection regulations, LTA requirements, and project contractual safety obligations.
• Carry out any additional safety-related duties as assigned by the WSHO, Project Manager, or Project Director.

Job Requirements:

• Diploma or Degree in Workplace Safety & Health, Engineering, Construction Management, Environmental Management, or related discipline.
• Valid WSH Coordinator Certificate recognised by MOM, Singapore.
• Experience in conducting safety training programmes.
• Minimum 5 years of WSH experience in construction projects.
• Experience in MRT / LTA / infrastructure projects will be an advantage.
• Familiar with WSH Act, subsidiary legislations, PTW system, RA & SWP implementation.
• Environmental Control Officer (ECO) certification will be an added advantage.
• Good communication and interpersonal skills with ability to engage site workforce and subcontractors.
• Able to work independently in a fast-paced construction environment.
• Willing to work at construction site and perform night shift / shift work when required.

Job duties and responsibilities:

• Design new products and continually improve existing products to meet industry standards and customer requirements.
• Develop technical manuals and Instruction Operating Manuals for products, ensuring accuracy and usability.
• Prepare, review, and verify design drawings, detailed specifications, and fabricated drawings for compliance with technical standards.
• Create Bills of Materials (BOMs) and ensure accurate documentation.
• Order materials and supplies; monitor the progress of fabrication and installation to ensure alignment with design specifications and schedules.
• Perform quality control checks to ensure the integrity of materials, components, and final products.
• Update and maintain design records, project databases, and documentation for traceability and reference.
• Track and coordinate the delivery of goods and materials to meet project timelines.
• Collaborate with cross-functional teams, including procurement, production, and project management, to address technical challenges.
• Provide technical support and guidance to the fabrication and installation teams during project execution.
• Identify opportunities for cost optimization, design innovation, and process improvement.

Job Requirements:

• Degree or Diploma in Mechanical, Precision, Tool, and Die Engineering, or a related field.
• At least 2 years of experience as a Design Engineer.
• Proficiency in drafting software such as AutoCAD, SolidWorks, 3D modeling software, or equivalent.
• Experience in Marine Hydraulic Applications, with knowledge of valves and actuators, as well as gear design (e.g., spur gear, planetary gear, bevel gear).
• Understanding of forging, casting, and precision CNC machining processes.

The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE prides itself in its excellent research capabilities in areas including advanced manufacturing, aerospace, biomedical, energy, industrial engineering, maritime engineering, robotics, etc. The school is equipped with state-of-the-art research infrastructure, housing a comprehensive range of cluster laboratories, test bedding facilities, research centres/institutes and corporate laboratories. Cutting-edge research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in developing new competencies to support the growth and competitiveness of our engineering sector in the global landscape. MAE has grown to be leader in Engineering Research, ranking amongst the top engineering schools in the world.

For more details, please view https://www.ntu.edu.sg/mae/research.

The research associate will focus on Vision-Language Model based situation awareness and decision-making for autonomous vehicles

Key Responsibilities:

• The research associate will be leading the development of Vision-Language Model based situation awareness and decision-making models for autonomous vehicles.

• The work will involve model training, test rig set-up, and experimental validation

Job Requirements:

• The candidate must at least have a Master Degree in AI, Robotics, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, etc.

• Strong background in AI, Large Language Model, autonomous driving, deep learning, interaction modelling, prediction, robotics and automation.

• Candidates having relevant research or working experience in LLM/VLM and AI decision-making algorithms for end-to-end autonomous driving will be preferred.

• Good communications skills and the ability to work independently and facilitate projects with minimal supervision.

• Able to contribute to Journal/Conference papers with good presentation skills.

• Able to plan and organize well and adhere to deadlines

We regret to inform that only shortlisted candidates will be notified.

Our third-party due diligence (VANTAGE) team assess our clients’ current, former or potential counterparties, looking for any issues that might pose a reputational or business risk to them, wherever they may be in the world. The work is compliance-focused and volume-driven.

The Associate Research Manager is responsible for the quality of VANTAGE work. S/he will oversee and guide Researchers to ensure they produce clear, analytical and exceptionally well-written reports which help our clients protect their integrity and reputation.

S/he will also support the Research Manager in training researchers and managing projects, leveraging internal and external resources in order to complete VANTAGE projects in a timely and effective manner. 

The successful candidate will have a strong knowledge of open-source intelligence and public record research, experience in writing and reviewing due diligence reports, people management skills and has excellent communication, writing and interpersonal skills.

People Management

• Manage a team of researchers and senior researchers
• Define, for each team member, objectives and responsibilities in line with the practice goals
• Conduct performance reviews
• Ensure well-being and professional development of staff
• Support the Research Manager in recruiting new researchers

Project management of third-party due diligence

• Ensure VANTAGE work is properly scoped, allocated to researchers, tracked and ultimately delivered on time and within budget
• Communicate directly with clients in order to clarify the scope of projects, address questions, and suggest potential additional avenues of research
• Review and approve (content and editorial) VANTAGE work, ensuring projects are of high quality and meet Clients’ specifications
• Liaise with and provide feedback to vendors and subcontractors, ensuring the quality of work they provide is high and adheres to our global delivery standards
• Engage with colleagues in the Business Intelligence team whenever VANTAGE work requires their input and collaboration

Regional research initiatives

• Assist Research Manager in training new researchers in the VANTAGE methodology and approach, ensuring new team members successfully complete the onboarding process
• Provide continual training and cascade updates to the VANTAGE methodology and approach
• Monitor quality of work and give feedback to researchers; motivate and guide researchers to ensure they are focused and directed effectively on operational and other aspects of the work
• Interact regularly with other Team Leads and Associate Research Managers to provide support and feedback on VANTAGE work
• Participate in discussions with other Team Leads and Associate Research Managers to provide insight on potential service/product improvement

• Education to degree level (minimum of a bachelor’s or equivalent experience)
• Full fluency in English written and spoken is essential

• Experience in writing, researching and reviewing/editing due diligence reports; demonstrated excellence in research, writing and editing in English
• Experience in managing projects, especially where the project team is spread across several locations
• At least 1-2 years’ experience in line management
• Strong knowledge of research techniques, databases, networks, online registers and archives and other OSINT research tools
• Experience influencing people across an organization, especially without direct reporting lines
• Proven ability to meet project deadlines

Preferred

• Knowledge of software-based case management solutions
• Experience in a compliance team in a financial institution or a corporate setting
• Knowledge of other languages and the socio-political environment in the region is an advantage
• Qualifications specific to financial crime or compliance would be an advantage

• Control Risks offers a competitively positioned compensation and benefits package that is transparent and summarised in the full job offer.
• We operate a discretionary global bonus scheme that incentivises, and rewards individuals based on company and individual performance.
• Control Risks supports hybrid working arrangements, wherever possible, that emphasise the value of in-person time together - in the office and with our clients - while continuing to support flexible and remote working.
• Working with our clients, from day one our people are given direct responsibility, career development and the opportunity to work collaboratively on fascinating projects in a rewarding and inclusive global environment.
• The Company is committed to further its diversity, inclusion and equity agenda and as an employee you have access to various business resource groups in the Company including the Company's LGBT+ network called MOSAIC, the Women's Network, and Synergy - a people network to celebrate and promote ethnic diversity at Control Risks

Control Risks is committed to a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

If you require any reasonable adjustments to be made in order to participate fully in the interview process, please let us know and we will be happy to accommodate your needs.

Responsibilities:

·       Lead the research and development of novel AI architectures that fuse vision data with temporal manufacturing process data to predict final product quality.

·       Develop advanced methodologies for Root Cause Analysis (RCA), moving beyond correlation to establish causal links between process variables and inspection outcomes.

·       Design and implement Knowledge Graphs and semantic reasoning layers that integrate domain expertise with LLMs/VLMs to automate "final sentencing" and provide explainable AI (XAI) insights.

·       Architect and fine-tune state-of-the-art multimodal models to enable text-prompt able vision inspection and contextual decision-making.

·       Pioneer the use of Temporal Transformers or Physics-Informed Neural Networks (PINNs) to analyze complex manufacturing time-series data for anomaly detection and yield prediction.

·       Document research in high-impact internal reports or patent filings and stay at the forefront of AI/ML literature to maintain the institute competitive edge.

·       Provide technical oversight for QC/QA governance frameworks and mentor junior engineers in data integrity and model validation.

 JOB REQUIREMENTS

·       Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related quantitative field is mandatory.
·       At least 2 years of experience

·       Demonstrated experience in publishing or developing innovative algorithms in Computer Vision, Predictive Analytics, or Multimodal AI.

·       Deep understanding of AI-based image segmentation, classification and time-series analysis and signal processing.

·       Hands-on experience with Knowledge Graphs, ontologies, or graph neural networks (GNNs).

·       Strong background in Root Cause Analysis (RCA) and statistical process control.

·       Advanced Python programming skills.

·       Ability to drive research projects from conceptualization to a deployable "target product."

·       Exceptional ability to communicate complex scientific concepts to both technical peers and non-AI manufacturing stakeholders.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

Responsibilities:

·       Lead the research and development of novel AI architectures that fuse vision data with temporal manufacturing process data to predict final product quality.

·       Develop advanced methodologies for Root Cause Analysis (RCA), moving beyond correlation to establish causal links between process variables and inspection outcomes.

·       Design and implement Knowledge Graphs and semantic reasoning layers that integrate domain expertise with LLMs/VLMs to automate "final sentencing" and provide explainable AI (XAI) insights.

·       Architect and fine-tune state-of-the-art multimodal models to enable text-prompt able vision inspection and contextual decision-making.

·       Pioneer the use of Temporal Transformers or Physics-Informed Neural Networks (PINNs) to analyze complex manufacturing time-series data for anomaly detection and yield prediction.

·       Document research in high-impact internal reports or patent filings and stay at the forefront of AI/ML literature to maintain the institute competitive edge.

·       Provide technical oversight for QC/QA governance frameworks and mentor junior engineers in data integrity and model validation.

 JOB REQUIREMENTS

·       Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related quantitative field is mandatory.
·       At least 5 years of experience

·       Demonstrated experience in publishing or developing innovative algorithms in Computer Vision, Predictive Analytics, or Multimodal AI.

·       Deep understanding of AI-based image segmentation, classification and time-series analysis and signal processing.

·       Hands-on experience with Knowledge Graphs, ontologies, or graph neural networks (GNNs).

·       Strong background in Root Cause Analysis (RCA) and statistical process control.

·       Advanced Python programming skills.

·       Ability to drive research projects from conceptualization to a deployable "target product."

·       Exceptional ability to communicate complex scientific concepts to both technical peers and non-AI manufacturing stakeholders.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE prides itself in its excellent research capabilities in areas including advanced manufacturing, aerospace, biomedical, energy, industrial engineering, maritime engineering, robotics, etc. The school is equipped with state-of-the-art research infrastructure, housing a comprehensive range of cluster laboratories, test bedding facilities, research centres/institutes and corporate laboratories. Cutting-edge research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in developing new competencies to support the growth and competitiveness of our engineering sector in the global landscape. MAE has grown to be leader in Engineering Research, ranking amongst the top engineering schools in the world.

For more details, please view https://www.ntu.edu.sg/mae/research.

The research fellow will focus on foundation model-based world model development for embodied intelligence, and robotics.

Key Responsibilities:

• The research fellow will be leading the development of foundation model-based world model development for embodied intelligence and robotics.

• The work will involve model development, model training, test rig set-up, and experimental validation.

Job Requirements:

• The candidate must at least have a PhD Degree in AI, Robotics, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, etc.

• Strong background in AI, Vision Language Model, end-to-end autonomous driving, deep learning, computer vision, robotics and automation.

• Candidates having relevant research or working experience in computer vision, VLM/VLA and end-to-end autonomous driving will be preferred.

• Good communications skills and the ability to work independently and facilitate projects with minimal supervision.

• Able to contribute to Journal/Conference papers with good presentation skills.

• Able to plan and organize well and adhere to deadlines

We regret to inform that only shortlisted candidates will be notified.

The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE prides itself in its excellent research capabilities in areas including advanced manufacturing, aerospace, biomedical, energy, industrial engineering, maritime engineering, robotics, etc. The school is equipped with state-of-the-art research infrastructure, housing a comprehensive range of cluster laboratories, test bedding facilities, research centres/institutes and corporate laboratories. Cutting-edge research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in developing new competencies to support the growth and competitiveness of our engineering sector in the global landscape. MAE has grown to be leader in Engineering Research, ranking amongst the top engineering schools in the world.

For more details, please view https://www.ntu.edu.sg/mae/research.

The research associate will focus on Vision-Language Model based situation awareness and decision-making for autonomous vehicles

Key Responsibilities:

• The research associate will be leading the development of Vision-Language Model based situation awareness and decision-making models for autonomous vehicles.

• The work will involve model training, test rig set-up, and experimental validation

Job Requirements:

• The candidate must at least have a Master Degree in AI, Robotics, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, etc.

• Strong background in AI, Large Language Model, autonomous driving, deep learning, interaction modelling, prediction, robotics and automation.

• Candidates having relevant research or working experience in LLM/VLM and AI decision-making algorithms for end-to-end autonomous driving will be preferred.

• Good communications skills and the ability to work independently and facilitate projects with minimal supervision.

• Able to contribute to Journal/Conference papers with good presentation skills.

• Able to plan and organize well and adhere to deadlines

We regret to inform that only shortlisted candidates will be notified.