Total 163 job vacancies by National University Of Singapore

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Job Description

• Conduct research in mechanical engineering.
• Design and prepare course materials, including syllabi, handouts, homework assignments and exams.
• Develop and deliver lectures on mechanical engineering topics or related disciplines.
• Engage in activities for student outreach and advice.

Qualifications

A PhD degree in Mechanical Engineering or related discipline

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

One Research Engineer position is open in the research group of Assistant Professor Zhao Lin, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The Research Engineer (RE) will work closely with the Principal Investigator (PI) on visual navigation foundation model for mobile robots, exploration using reinforcement learning control, learning-based control, etc. The RE will develop and train algorithms that enable intelligent and robust autonomous navigation in unseen environments. Hardware experiments will be carried out to test and demonstrate the applications of the developed algorithms.

The initial appointment duration is 12 months, which can then be extended based on an evaluation at the end of the initial appointment.

The candidates should have a Master’s degree from a reputable university, with expertise in robot learning, reinforcement learning, and aerial robotics.

A successful candidate should have a solid mathematical background (such as in calculus, linear algebra, ODE/PDE, optimization, real analysis, probability theory, stochastic process, etc). Strong publication records in leading journals and conferences of the relevant fields, and practical hands-on experience in applying visual foundation models to real mobile robots are required.

Qualifications

• Possess a master’s degree in Computer Engineering/Science or strictly related (e.g., either Electrical Engineering, Mathematics, Communication, Mechanical, etc.)
• Have research experiences in computer vision, vision foundation model, control theory, reinforcement learning.
• Possess a strong academic record proved through coursework (especially math-intensive courses) and projects during his/her undergraduate and master’s studies.
• Proficient in C++ or Python. Familiar with machine-learning tools and packages. Familiar with various 3D simulation environments for quadrotor simulations. Familiar with ROS and quadrotor control algorithms.
• Have well-established analytical and problem-solving skills, as documented by publications that are relevant to the field of robot navigation, reinforcement learning control for robotics applications.
• Excellent communication skills as he/she is required to publish and present results at conferences and journals independently.
• Activity performed in world-class research environments is highly valued.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

One Research Engineer position is open in the research group of Assistant Professor Zhao Lin, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The Research Engineer (RE) will work closely with the Principal Investigator (PI) on visual navigation foundation model for mobile robots, exploration using reinforcement learning control, learning-based control, etc. The RE will develop and train algorithms that enable intelligent and robust autonomous navigation in unseen environments. Hardware experiments will be carried out to test and demonstrate the applications of the developed algorithms.

The initial appointment duration is 12 months, which can then be extended based on an evaluation at the end of the initial appointment.

The candidates should have a Master’s degree from a reputable university, with expertise in robot learning, reinforcement learning, and aerial robotics.

A successful candidate should have a solid mathematical background (such as in calculus, linear algebra, ODE/PDE, optimization, real analysis, probability theory, stochastic process, etc). Strong publication records in leading journals and conferences of the relevant fields, and practical hands-on experience in applying visual foundation models to real mobile robots are required.

Qualifications

• Possess a master’s degree in Computer Engineering/Science or strictly related (e.g., either Electrical Engineering, Mathematics, Communication, Mechanical, etc.)
• Have research experiences in computer vision, vision foundation model, control theory, reinforcement learning.
• Possess a strong academic record proved through coursework (especially math-intensive courses) and projects during his/her undergraduate and master’s studies.
• Proficient in C++ or Python. Familiar with machine-learning tools and packages. Familiar with various 3D simulation environments for quadrotor simulations. Familiar with ROS and quadrotor control algorithms.
• Have well-established analytical and problem-solving skills, as documented by publications that are relevant to the field of robot navigation, reinforcement learning control for robotics applications.
• Excellent communication skills as he/she is required to publish and present results at conferences and journals independently.
• Activity performed in world-class research environments is highly valued.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

One Research Engineer position is open in the research group of Assistant Professor Zhao Lin, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The Research Engineer (RE) will work closely with the Principal Investigator (PI) on visual navigation foundation model for mobile robots, exploration using reinforcement learning control, learning-based control, etc. The RE will develop and train algorithms that enable intelligent and robust autonomous navigation in unseen environments. Hardware experiments will be carried out to test and demonstrate the applications of the developed algorithms.

The initial appointment duration is 12 months, which can then be extended based on an evaluation at the end of the initial appointment.

The candidates should have a Master’s degree from a reputable university, with expertise in robot learning, reinforcement learning, and aerial robotics.

A successful candidate should have a solid mathematical background (such as in calculus, linear algebra, ODE/PDE, optimization, real analysis, probability theory, stochastic process, etc). Strong publication records in leading journals and conferences of the relevant fields, and practical hands-on experience in applying visual foundation models to real mobile robots are required.

Qualifications

• Possess a master’s degree in Computer Engineering/Science or strictly related (e.g., either Electrical Engineering, Mathematics, Communication, Mechanical, etc.)
• Have research experiences in computer vision, vision foundation model, control theory, reinforcement learning.
• Possess a strong academic record proved through coursework (especially math-intensive courses) and projects during his/her undergraduate and master’s studies.
• Proficient in C++ or Python. Familiar with machine-learning tools and packages. Familiar with various 3D simulation environments for quadrotor simulations. Familiar with ROS and quadrotor control algorithms.
• Have well-established analytical and problem-solving skills, as documented by publications that are relevant to the field of robot navigation, reinforcement learning control for robotics applications.
• Excellent communication skills as he/she is required to publish and present results at conferences and journals independently.
• Activity performed in world-class research environments is highly valued.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

• Lead, oversee, and plan the development of autonomous vehicle learning platforms.
• Identify and develop autonomous vehicle hardware and software stacks.
• Actively drive projects to improve existing platform features and add new features to complement and expand the capabilities of the system.
• Engage and mentor Master’s and Undergraduate students as well as industry attachment interns.
• Collaborate with other research engineers and coordinate various activities at the Advanced Robotics Centre.

Qualifications

• Bachelor’s degree in engineering related to robotics field.
• Familiar with vehicle structures, electronics, vehicle kinematics and dynamics.
• Experience with autonomous vehicles Drive-by-Wire (DBW) systems and control.
• Proficiency in CAD/CAM and fast prototyping.
• Familiar with open-source autonomous driving frameworks such as Apollo, Autoware, etc.
• Proficiency in robotics middleware and simulation tools (ROS, Gazebo, Carla, SUMO, Carsim (preferred)).
• Experience in C/C++ and Python development.
• Experience in autonomous vehicles and robotics full-stack development is preferred.
• Experience in remote control system development is preferred.
• Highly motivated individual who can work in a fast-paced environment.
• Meticulous organizer with a positive and can-do attitude.
• Strong team player with the ability to lead projects.
• Good communication, writing and presentation skills.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking a motivated and skilled Research Assistant to join our team, focusing on the development and characterization of advanced 2D materials. The successful candidate will play a key role in supporting projects related to the growth, optimization, and detailed analysis of thin films for next-generation electronic devices.

Key Responsibilities:

• Materials Growth and Synthesis: Conduct thin-film deposition using techniques like Chemical Vapor Deposition (CVD) to synthesize 2D materials like MoS2 and other materials. Optimize growth parameters to achieve desired thickness, crystallinity, and uniformity.
• Characterization and Analysis: Utilize Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), and Raman spectroscopy for in-depth material characterization, focusing on morphology, surface roughness, grain size, and crystallinity.
• Data Collection and Analysis: Systematically document experimental procedures, collect data, and analyze results. Interpret findings to drive improvements in synthesis protocols and optimize film properties.
• Research Documentation: Prepare comprehensive reports, summarize research findings, and present data to support ongoing projects and publications.
• Collaboration and Lab Support: Work closely with team members, provide support for collaborative experiments, and maintain laboratory equipment.

Qualifications

• Master’s degree in Materials Science, Chemistry, Physics, or a related field.
• Demonstrated experience with CVD, AFM, SEM, and other characterization tools for thin films and nanomaterials.
• Proficiency in handling 2D materials with a strong focus on growth and sulfurization processes.
• Ability to work independently and collaboratively, with excellent attention to detail and problem-solving skills.

This position offers a unique opportunity to contribute to cutting-edge research in materials science, focusing on 2D materials for advanced electronics. If you have a strong foundation in materials synthesis and characterization and are eager to develop innovative solutions, we encourage you to apply.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

About the Centre for Quantum Technologies (CQT)

The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. Experts in this new discipline of quantum technologies are applying their discoveries in computing, communications, and sensing.

CQT is hosted by the National University of Singapore. The Centre also has staff at the Agency for Science, Technology and Research, Nanyang Technological University, Singapore, and the Singapore University of Technology and Design. With some 200 staff and students, it offers a friendly and international work environment

Learn more about CQT at www.quantumlah.org

Job Description

The Centre for Quantum Technologies (CQT), National University of Singapore is looking for researchers and engineers to develop next generation quantum computers based on trapped ions. There are multiple positions available at different levels with a diverse set of expertise. This program is funded under the National Quantum Processor Initiative, a flagship program under the National Quantum Office Singapore. The aim of the program is to develop a full stack quantum processor based on Yb-Ba ions. This program brings together the unique capabilities of the existing ion trap groups in CQT expertizing on these two-ion species to explore scalability of the system.

The Centre for Quantum Technologies is a pioneering quantum centre in the world offering a diverse research culture at the intersection of three different fields namely, theoretical, experimental Physics and computer science. We offer competitive salary and enriching intellectual experience in a city state known for its forward outlook. This program also allows strong collaboration with leading academic and industrial groups within and outside the country.

The team members will work to build electronics to control the ion trap quantum processor. That includes digital design, RF and microwave sources and low noise analog / digital front end. The ideal candidate should have practical experience in at least one of the following fields and desire to cross the boundaries and learn relevant skills.

The successful candidate will be involved in all stages of the development cycle: collaborate with other team members to define the technical requirements, design, manufacturing, testing and integration of the prototype into the control system.

Job Requirements

We are looking for several electrical engineers to join the small team of scientists and engineers working on the next generation of the ion trap quantum processor. The candidate should have:

• Bachelor or Master degree in electronics, electrical engineering or related fields;
• At least 1-2 years of experience in electronics design is preferred;
• Experience in programmable digital logic design using Verilog or VHDL, digital signal processing, and familiarity with control theory;
• Design and characterisation of low noise electronics for the analog front end, good understanding of the noise sources in electronic circuits;
• Design and implementation of the RF electronics circuits.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

About NUS IT

NUS Information Technology is the cornerstone to providing reliable, high-performance and secure IT solutions and effective IT governance for the campus. Here at NUS IT, we aim to transform NUS into a borderless computing community providing knowledge at its fingertips by enhancing the use of effective applications and services for teaching and learning.

We drive a culture that is forward-looking. With a strong passion for IT, our people are always striving to improve, push boundaries and innovate with a "can-do" attitude. We embrace collaboration, open communication and knowledge sharing. If you see yourself thriving in a dynamic environment and breaking new grounds with innovative ideas, you will find yourself at home in NUS IT.

As part of our team, you can look forward an empowered work environment that allows you to take charge of your own career path. We provide competitive remuneration as well as flexible work arrangements to enable your growth and development. We pride ourselves on our diverse workforce and are committed to transforming NUS into a leading global University shaping the future.

https://nusit.nus.edu.sg/

Job Description

We are seeking an experienced Data Engineering Lead to oversee the data engineering team in NUS.

The role will be responsible for leading and guiding teams in the development of high-quality data lakehouse, ensuring they meet business needs and align with NUS strategic goals. The role will also ensure the proper implementation across all stages of the data lifecycle

This role will manage a team of 6 data engineers handling ELT/ETL framework and end-to-end data pipelines from various source systems to data lakehouse with a plan for future growth.

This is a hands-on leadership role and the candidate should have been on active hands-on development at least 5 years prior.

Duties and Responsibilities

Technical Expertise
• Participate in the technical design of data platforms and their technologies, including their framework, architecture, standards, and guidelines.
• Provide technical guidance and expertise to the team, helping to solve complex technical challenges.
• Stay updated about emerging technologies and industry trends to drive innovation within our organization.
• Ensure adherence to best practices in design, development, testing, and maintenance.
Leadership and Team Management
• Lead and mentor the team, fostering a culture of innovation, collaboration, and excellence.
• Provide direction and guidance to the team in managing the full data lifecycle.
• Perform Scrum Master role for the team.
• Develop and implement strategies to enhance team’s performance and productivity.
• Foster collaboration and high-performance culture within the team.
Delivery Management
• Ensure timely and high-quality delivery, aligning with project objectives, scope, and timelines.
• Oversee the design and implementation of data lakehouse to meet the university’s needs.
Quality Assurance
• Implement quality control and testing procedures to guarantee the high-quality delivery.
• Ensure data lakehouse aligns with the university's regulatory and compliance requirements.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Minimum of 7 years of experience in technical leadership roles, with a strong emphasis on data lakehouse and data engineering solutions.
• Proven ability to lead data engineering teams, promoting collaboration and achieving project objectives.
• Strong problem-solving and critical-thinking skills, with a proven track record of effectively addressing technical challenges and risk mitigation.
• Strong knowledge of quality assurance processes, encompassing testing methodologies, and quality control procedures.
• Relevant experience in designing, developing, and supporting data lakehouse and data engineering solutions.
• Strong verbal, written and interpersonal communication skills with the ability to interact and communicate effectively with all levels of management, users, and vendors.
• Must be a good team player, proactive in nature, fast learner, highly organized and go-getter attitude with can-do spirit.

Technical Expertise
• Strong working experience in end-to-end development of data lakes and data warehouses, preferably with experience in Informatica.
• Strong working experience in Azure Data services, preferably Azure Fabric.
• Strong database working experience for transactional and analytics systems, including querying and tuning large, complex data sets and performance analysis.
• Working experience in big data and DataSecOps is an added advantage.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

The Research Engineer will be involved in developing computer models for assessing climate change impacts on marine ecosystems. He/she will also be involved in collecting field data for calibrating and validating model systems. In addition to the above, the Research Engineer is expected to also participate actively in research meetings, present research findings, write reports and research papers.

Job Requirements

• Possess at least a good Bachelor’s degree in Civil and/or Environmental Engineering or equivalent.
• Experience in computational modelling in environmental engineering or climate change is preferred.
• Open to fixed term contract

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

Tenure-track faculty positions in Geotechnical Engineering, on areas related to Urban Sustainable Development and Climate Change. Faculty members will be expected to teach existing undergraduate and graduate courses as part of the Civil and Environmental Engineering curricula, as well as develop new and innovative courses related to geotechnical engineering and sustainability.

Job Requirements

The candidate should hold a doctorate in civil engineering or a closely related discipline, preferably with background and experience in, but not limited to, one or more of the following geotechnical domain expertise: underground space, land creation, sustainable geo-materials and coastal resilience. Additional skills and knowledge in centrifuge modelling, data analytics and machine learning will be highly advantageous. The ability to develop and maintain an active and externally funded research programme within his/her area of expertise will be an added advantage.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

You will work as an integral part of the laboratory operations team, providing support to the laboratory manager in operations and related laboratory duties such as safety matters, procurement and core equipment training. If you thrive in a dynamic environment and have a passion for managing laboratory operations and contributing to scientific advancements, this role could be an exciting fit for you!

Key Responsibilities

• Oversee the daily operations of the laboratory, ensuring that all processes and procedures are followed accurately and efficiently
  Facilitate training and development of laboratory users
  Support the operations team on laboratory safety and documentation
  Ensure compliance with all relevant regulations and safety standards to maintain a safe working environment
  Manage the laboratory procurement of equipment and supplies, including negotiating contracts with vendors and suppliers
  Implement and oversee maintenance schedules for laboratory equipment to ensure optimal performance and longevity
  Maintain the microfabrication cleanroom in functional state
  Stay abreast of technological advancements to enhance operational effectiveness.
  Other ad-hoc duties

Qualifications

• Bachelor’s Degree in Engineering or related field from a reputable university
• At least one year of working experience in a research/laboratory environment and familiarity with research operations
• Working experience in rapid prototyping, CAD or cleanroom microfabrication is preferred, but not necessary
• Understanding of safety regulations and compliance
• Ability to work cooperatively and communicate effectively with team members and researchers
• Passionate in mastering research equipment and passing on knowledge to users

To apply, please send your cover letter, CV and three references (name, institution, email). Only shortlisted candidates will be contacted.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

The job holders are to work with PI and the research team to process air quality data and study small-scale dispersion of airborne pollutants in urban environment.

Qualifications

One or more of (but not limited to) the following:

• Bachelor Degree in Engineering or relevant field
• Experiences of (small-scale) simulations of air pollutant dispersion, meteorology modelling, data processing
• Demonstrating as a fast learner of conducting literature study and literature summary
• Experiences of handling big data via R, Python, Matlab, etc.
• Experience with UNIX-based operating systems and bash script or similar
• Strong interests in applying machine learning models and applications to atmospheric research
• Proactive in assisting and contributing to quality scientific research publications
• Proficient in technical presentation, slide making, report writing, etc.
• Proven rounded and effective team player with strong initiative and ownership of the research project

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

The Institute of Operations Research and Analytics (IORA) is seeking a dedicated and skilled Research Engineer to support our research projects focused on the implementation and analysis of machine learning (ML) algorithms. The successful candidate will be instrumental in providing coding expertise, data management, and analytical support to a range of projects in operations research and analytics.

This is an excellent opportunity for recent graduates passionate about applying their technical skills to real-world problems, particularly in the field of machine learning and data analytics.

Key Responsibilities

• Coding and Implementation: Develop and implement machine learning algorithms and models to support IORA’s ongoing and new research projects.
• Data Analysis: Conduct data processing, exploration, and visualization, delivering insights that guide research conclusions.
• Model Evaluation: Collaborate with researchers to evaluate model performance, optimizing algorithms for robustness and efficiency.
• Documentation: Ensure thorough documentation of code, data pipelines, and research findings to facilitate reproducibility and project continuity.
• Collaboration: Work closely with research teams to understand project objectives, gather requirements, and provide technical support in the form of coding and data analysis.
• Maintenance and Troubleshooting: Manage and troubleshoot issues in codebases and data pipelines as they arise, ensuring smooth and efficient project progress.

Requirements

• Education: Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, or related field.
• Programming Skills: Proficiency in Python (preferred) or R, with experience in relevant libraries for ML and data processing (e.g., Scikit-Learn, Pandas, TensorFlow, PyTorch).
• Data Management: Familiarity with data extraction, cleaning, and preprocessing methods; experience with SQL or other database management tools is a plus.
• Machine Learning Knowledge: Understanding of machine learning fundamentals, including supervised and unsupervised learning, model selection, and evaluation techniques.
• Analytical Mindset: Strong analytical and problem-solving skills with attention to detail in data analysis and algorithm implementation.
• Team Collaboration: Ability to work collaboratively within a research environment, with effective communication skills to convey technical information clearly.

Preferred Experience

• Experience with version control systems, such as Git.
• Prior research experience or involvement in machine learning or data science projects is advantageous.
• Exposure to cloud computing platforms like AWS or GCP for ML model deployment (optional but a plus).

How to Apply

Interested applicants should submit their resume, a cover letter detailing their interest in the role, and any relevant project portfolios or coding samples that demonstrate their experience with ML and data analysis.

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

Genetic engineering of plants promises to provide sustainable solutions for food security and climate change mitigation. Current genetic engineering technologies using Agrobacterium, viruses and nanoparticles through syringe injection and biolistic bombardment suffer from limitations including narrow ranges of host species, low transformation efficiencies, strict restrictions on cargo types and sizes, tissue damage and unwanted transgene integration into plant genome. A major challenge to deliver exogenous material into plants is the cell wall barrier. The Tay lab will be hiring a research fellow to develop nanomaterials for plant genetic engineering, with the goal to produce plants with enhanced traits such as higher yield and weather-resistant.

Conducting experiments, writing manuscripts

Qualifications

PhD in materials engineering or plant biology; 2 first author papers; ideally, experience in in vivo and in vitro plant work

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

• To perform safety-related work such as

(a) Conduct safety training / briefing for personnel who needs to work in the cleanroom;

(b) Carry out periodic emergency response drill to familiarize personnel with standard evacuation and response procedure;

(c) Carry out periodic inspection of safety facility such as eyewash & shower, chemical spill absorbent, fire extinguisher, etc.

(d) To monitor users’ activities on CCTV for any irregularities.

• To respond to an emergency call during and after office hour. The emergencies can be a building fire alarm, a fab evacuation alarm which can be a hazardous material spill or a leak or a medical emergency situation.
• To assess the situation and discuss a coordinated response plan with both Safety Manager and Lab Manager based on Emergency Response Plan (ERP)
• To be on standby / on-site for ad-hoc / extended hours lab operations request;
• To learn and have some understand of the chemistry for each individual tools and new projects to ensure Industrial Hygiene for the lab and users are met.
• To follow up, understand changes and make assessment on the safety aspect for tool continuous improvement process (CIP)
• To liaise with supplier for maintenance / procurement of ERT equipment / supplies;
• To perform risk assessments for the research activities related to E5 Cleanroom process and equipment.
• Support the development and implementation of Safety & Health Management System for AMAT-NUS Corp Lab conducting materials research.
• To support on Safety audits
• Any other duties as assigned.

Qualifications

• Diploma/ Degree knowledge and demonstrated experience in the laboratory safety management.
• Awareness of local safety regulations and some experience in developing and implementing Workplace Safety & Health Management System and Programmes.
• Understanding of the scientific and safety-related issues of materials research protocols and ability to review the risk assessments of such protocols.
• Knowledge and understanding of material safety principles, policies, and procedures.
• Effective communication (verbal and technical writing) skills, excellent customer service skills with attention to detail.
• Well verse with Microsoft office and good documentation control. IT application knowledge will be an advantage.