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

A 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 will work closely with the Principal Investigator (PI) on quadrotor path planning, control, SLAM, swarm path planning, and cooperative transport. The approach will leverage the advantages of both deep reinforcement learning and conventional controls, combining model-based and model-free methods. Strong hardware experience and C++ coding especially related to quadrotor path planning and control are required.

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 Bachelor’s or Master’s degree from a reputable university, and with strong hardware expertise in aerial robotics.

A successful candidate should have a solid mathematical background (such as in calculus, linear algebra, optimization, etc.). Strong publication records in leading journals and conferences, and practical hands-on experience in applying reinforcement learning to real robotics applications (e.g., autonomous driving and unmanned aerial vehicles) are highly valued.

Qualifications

• Possess a bachelor’s or master’s degree in either Electrical Engineering or strictly related (e.g., Mathematics, Computer, Electrical, Mechanical, Information Engineering).
• Have research experiences in control, reinforcement learning, distributed optimization, multi-agent, UAVs.
• Possess a strong experience in practical hands-on hardware project, familiar with 3D modelling and mechanical design. 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 algorithm.
• Have well-established analytical and problem-solving skills, as documented by publications that are relevant to the field of control theory and robotics applications, 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.
• 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

The Department of the Built Environment at the National University of Singapore hosts the Centre for 5G Digital Building Technology (5GDBT), which focuses on several key research areas. These include:

1. Smart Facilities Management (FM) through Digital Twin (DT) technology.
2. Integration of Robotics and Internet of Things (IoT) sensors.
3. Exploration of Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (XR).
4. Advancements in 5G Network Technology.
5. Implementation of a Common Data Environment for the integration of Smart Technologies.

The primary objective of the Centre for 5GDBT is to play a pivotal role in Singapore's digital research transformation, aligning with the nation's goal of achieving nationwide 5G coverage by 2025. The Centre for 5GDBT aspires to become a leading hub for digital building technology, focusing on impactful research, comprehensive education, and the adoption of best practices. Its strategy involves leveraging 5G connectivity, cloud-based DT technology, and robotics for applications in Smart FM and the Built Environment (BE) industry. Ultimately, the Centre seeks to revolutionise the design, delivery, and management of Singapore's BE.

The Centre for 5GDBT is in search of a Research Fellow (RF) with a proven ability to lead and execute research projects independently. The role requires a strong foundation in managing research projects and a deep understanding of smart technologies within the Built Environment (BE) industry, specifically in the Facilities Management (FM) domain. This encompasses expertise in technological competencies and smart technologies such as robotics (e.g., cleaning robots, concierge robots) and IoT devices.

The RF will be tasked with not only the technical aspects of research projects but also administrative and managerial responsibilities associated with them. Additionally, they will play a crucial role in supporting PhD students by offering academic and research guidance, collaborating closely with the Principal Investigator (PI), Dr Shah. Ideal candidates should bring substantial research experience in relevant fields, possess robust data analysis skills, and demonstrate proficiency in programming.

The selected candidate will engage in both academic development and hands-on fieldwork, collaborating with fellow research staff and students. This will be carried out under the guidance and supervision of the Principal Investigator (PI).

Job Requirements

- Hold or be in the process of obtaining a Ph.D. (i.e. is in the final stages of PhD studies meaning submitted thesis or pending oral defence) in a relevant field, such as Computer Science, Building Science, or related disciplines.
- Demonstrate a proven track record in effectively managing and actively participating in advanced theoretical and computational research projects.
- Able to develop robotic use-cases for Smart Buildings and Smart Facilities Management
- Working with integration of Digital Twins with Robotics and IoT sensors
- Possess strong programming skills, with specific knowledge or experience in the areas listed below:
• Digital Twin
• Robots = Message Queuing Telemetry Transport (MQTT), Robot Operating System (ROS) 1 & 2, Python, Java, C++
• Cameras = Localised LAN Server, Video Management Server (VMS), Streaming RTMP
• Display = Remote PC Display
• Experience in API, APKs, SDKs, UI/UX
• Experience in Artificial Intelligence (AI), ChatGPT, Video Analytics
• Developer:
(1) AI detection models for Andriod
(2) Video Analytics (MobileNet, TensorflowLite, Kotlin)
(3) Andriod Apps Developer
(4) Live Streaming Andriod Apps
(5) Live Broadcasting Andriod Apps
(6) Backend Video Server Developer
- Skills listed below would be strongly preferred:
• Video Analytics Detection Models
• Large Language Models (LLM)
• Artificial Neural Networks
- Working with integration of Digital Twins with Robotics and IoT sensors, Generative AI, Smart Cameras, Drones
- Exhibit exceptional communication skills, both written and verbal, and demonstrate proficiency in team management. The candidate should also showcase independent problem-solving abilities.
- Fluency in oral and written English is essential to effectively collaborate and communicate within a diverse research environment.
- Experience in writing proposals and paper publications
- Ability to contribute to and lead the development of academic papers for publication in reputable and high-impact journals, reflecting a commitment to scholarly excellence.
- Proven capability to mentor and guide research staff and students, fostering a collaborative and innovative research culture.
- Display a keen interest in staying abreast of emerging technologies and methodologies within the specified research areas, continuously contributing to the intellectual advancement of the team.
- Previous experience in securing research funding, collaborating with industry partners, and participating in interdisciplinary research initiatives would be considered advantageous.

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

NUS is seeking for Research Engineer to work on the following topics.

1. Emerging Low-Carbon Technologies: Uncovering the carbon mitigation potential and cost-effectiveness of deployment of green hydrogen, CO2 capture and utilization, renewables-based heating, etc., in hard-to-abate sectors such as steel, cement, chemicals, and aluminum.

2. Existing Symbiotic Technologies: Exploring the deployment strategies of existing technologies related to industrial symbiosis and material/energy recycling to foster industrial synergy and collaborative infrastructure systems for increased sustainability.

Job Requirements

• Possess a bachelor degree in environmental science, energy, chemical engineering, economics, or other related fields.
• Good written and spoken communication.
• Excellent communication skills and capability to present research findings in publications.
• Open to fixed-term contract.

Note: Applications should include in a single .pdf file:

(i) Resume
(ii) Research statement (1-2 pages), including research summary and plans &
(iii) contacts of 3 reference persons plus the contact of your PhD supervisor.

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

• Pulsed plasma actuators have gained significant traction in the research community for their ability to produce enhanced aerodynamic performance with minimal modifications required to the system geometry. Yet while most studies have focused on flow separation control, less attention has been devoted to skin friction reduction. This project aims to examine and optimize the performance of a novel class of pulsed plasma actuators.
• The selected candidate is expected to conduct experiments to characterize both the aerodynamic performance and plasma properties of these actuators, so as to understand the underlying physical mechanisms leading to any observed drag reduction. Extensive use and development of laser-based techniques should be expected, along with ample potential for use of machine learning approaches.

Qualifications

• PhD in Fluid Mechanics, Aerodynamics, Applied Physics, Plasma Physics, or related field. Experience in laser-based diagnostics and/or machine learning approaches is strongly preferred.

Work location: Caldecott

Contract duration: 1 year

Salary: $2800

Responsibilities

• Assisting in project management of various research studies and research processes
• Liaising with internal and external stakeholders
• Participating in planning of research related events
• Developing digital material (e.g., infographics) to support research communications
• Assisting in fieldwork and/or analysis of research studies

Requirements

• Degree
• Strong project and event management, communication, and interpersonal skills
• Comfortable with a fast-paced team environment and multitasking
• Interest in social policy and research
• Familiar with graphic design software (e.g., Adobe Illustrator)
• Familiarity with social research methods (qualitative and/or quantitative) would be a strong advantage

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