Total 13 construction quality control job vacancies in Education / Training category in D19 Serangoon Garden, Hougang, Sengkang, Punggol

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

Research Fellow 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 Fellow will work closely with the Principal Investigator (PI) on theories and applications of learning-based control. The project will investigate and develop both deep reinforcement learning algorithms and conventional robust adaptive control methods, to develop safety-critical learning-based control algorithms that leverage the advantages of both model-based and model-free methods. In particular, the developed algorithms will be demonstrated through robust control of drones.

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 will be responsible for conducting theoretical research and algorithm development. The candidates are expected to help the PI supervise junior PhD students as well.

The candidates should have a Ph.D. degree from a reputable university, with expertise in robust adaptive control, reinforcement learning theory, collision-avoidance trajectory optimization, etc.

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 are required.

Qualifications

• Possess a Ph.D. Degree in either Electrical Engineering or strictly related (e.g., Mathematics, Computer, Communication, Mechanical, or Information Engineering).
• Have substantial research experiences in robust adaptive control, reinforcement learning, learning-based control, model predictive control, etc.
• Possess a strong academic record proved through coursework (especially math-intensive courses) and projects during his/her undergraduate and doctoral studies.
• Strong publication records in leading journals and conferences are highly valued
• Excellent communication skills as he/she is required to publish and present results at conferences and journals independently.
• Have well-established analytical and problem-solving skills, as documented by publications that are relevant to the field of reinforcement learning and control for robotics applications.
• 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

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 Research Fellow will work closely with the Principal Investigator, Dr. WU Zhe, on several research projects of optimization of chemical and manufacturing processes through machine learning tools
• The Research Fellow will help to develop both theoretical and simulation study of machine-learning-based control and optimization algorithms to chemical processes.

Job Requirements

For Research Fellow Position:

• A PhD degree in a relevant area, e.g., Control Engineering, Chemical Engineering, Automation, Systems Engineering, Computer Science or Applied Mathematics;
• Good publication record;
• Experienced in advanced process control, machine learning, and programming languages (e.g., python, Matlab, C++, etc)

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.

The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of the research team to develop a first-of-its kind AI-assisted integrated NDT verification system for reusability of structural steel with accuracy of ±10% at confidence level of 95%. The key innovation is to use AI to analyse a bigger data set and build a multi-parameter machine learning (ML) model that integrate the complex mechanical properties obtained from DT and the electric/magnetic permeability data obtained from NDT to predict the critical material characteristics of reusable steels.

Key Responsibilities

• Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.
• Undertake these responsibilities in the project:
  1. Establishing test result database: Conducting both DTs and NDTs on the same samples to create a comprehensive dataset for AI model development, managing data collection processes on-site at the collaborator’s factory, and ensuring the accuracy and integrity of the collected data.
  2. Developing statistical model: Utilizing DT results to develop statistical models for estimating mechanical characteristics based on normal distribution and analyzing statistical data to support model development.
  3. Developing and verifying the AI model: Developing various regression models and evaluate their feasibility and suitability, conducting model fitting and verification phases using training and test datasets and ensuring the selected model meets the accuracy criteria (±10% at 95% confidence) for individual mechanical characteristics and overall classification results (grade determination).
  4. Validation of the method: Implementing the proposed method and AI model in test bedding cases, measuring the impact of the method in terms of time and cost savings and developing implementation guidelines based on validation results.
• Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
• Coordinate procurement and liaison with vendors/suppliers.
• Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.
• Publish research findings in peer-reviewed journals and present at conferences.
• Assist in the preparation of project reports, proposals, and documentation.

Requirements

• Have relevant competence in the areas of structural engineering, material science, statistics and programming basics.
• Have a degree in Civil Engineering, Mechanical Engineering or Material Science. Possessing a Master’s or PhD degree will be advantageous.
• Knowledge of AI / ML and common ML programming languages will be advantageous.

Key Competencies

• Able to build and maintain strong working relationships with people within and external to the university.
• Self-directed learner who believes in continuous learning and development
• Proficient in technical writing and presentation
• Possess strong analytical and critical thinking skills
• Show strong initiative and take ownership of work
• Able to carry out data preprocessing, develop statistical and regression models.
• Possess knowledge of the mechanical properties of structural steel and factors affecting its performance
• Able to prioritize tasks, meet deadlines, and manage multiple responsibilities.

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 conduct research characterizing airborne pollutants in urban environment.

Qualifications

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

• Experience in applying data analytics, machine learning and handling big data
• Experience in applying Pythons functions of matplotlib, and numPy, pandas, statsmodels
• Fast learner - capable of conducting independent research and proficient literature search, review & summary with strong background in Chemical Engineering / Chemistry / Physics
• Experience in operating instruments measuring physical and/or chemical properties of airborne pollutants
• 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

This position involves working on a project related to climbing robots and their application for port operations. The objective of this position includes developing a climbing robot control system and designing the corresponding hardware, to control a climbing robot can climb on the containers and function as a lashing bar. The role involves the opportunity to work with the research team within National University of Singapore in which the team leaders are from the Department of Mechanical Engineering, alongside Specialists from a high technology company. The successful candidate will be self-motivated with an outstanding track record in robotics, control, computer science, or related disciplines. The main research tasks for the project include but will not be limited to:

• Designing and developing electronics hardware for an articulated vertical climbing robot.

• Implementing the control system on hardware and conducting tests in real-world outdoor environments

Qualifications

• Good coding skills in C/C++

• Experience with hardware and electronics/circuit design

• Experience with embedded system (Arduino, STM32, etc.)

• Literature review/summarizing skills

• Good writing/spoken communication 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

The job holder is to work with PI and the research team to conduct research characterizing VOCs in urban environment.

Job Requirements

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

• Well versed in operating PTR-TOFMS, maintenance, troubleshooting and data analyses
• Experience in handling big data via R, Python, Matlab, etc.
• Experience in laboratory (offline) VOC speciation and quantification
• 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

The candidate will be working on projects related to vessel electrification and underwater robot.

Job description

1. Implement state-of-the-art techniques and tools such as data-driven modelling, AI, deep learning, machine learning etc, to solve challenging problems.

2. Perform dynamic modelling of physical systems, control design and the coupling of numerical and physical systems applied to electric vessels, underwater Robotics and/or other systems operating in the ocean environment.

3. Develop hardware and software control architectures, sensing systems to support R&D in the areas of offshore hydrodynamics and fluid-structure interactions. This includes developing, testing, troubleshooting software and verification procedures.

4. Develop engineering requirements, specification and validation criteria for high-quality research using combinations of physical experiments, sensing, numerical simulations as well as data analytics to develop integrated physical-numerical modelling, simulations and applications.

5. Survey literature and implement state-of-the-art techniques and tools (such as AI, deep learning, machine learning, etc) to solve challenging problems.

6. Collaborate with industry partners, affiliated research institutes and other relevant stakeholders to contribute to grant proposals for research funding consistent with the strategic goals of TCOMS.

7. Any other duties as assigned by supervisor.

Job Requirements

Qualification & Field of Study:

The candidate should have a background in engineering / computing or related fields.

Other Requirements:

· Good interpersonal and communications skills.

· Ability to adapt and work effectively as members of a team.

· Resourceful and self-driven with a high degree of professional integrity.

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.

Job Description

Validate the TC&IS Development, Configuration, Validation and Management Plan application. Day-to-day, you’ll work closely with teams across the business (systems), achieve the specified software quality requirements detailed in System Engineering and TCMS Software Quality Plan and informs the team members of their associated responsibilities and much more.

• Specifically take care of managing the development of all Train Control & Information Systems (TC&IS) deliverables (sub-system, electrical and software work products) for a Project from offer, specification, design ,validation to end of warranty period, but also ensuring the quality on all domain of his/her project (Schematic, Apparatus, Software…).
  
  Your Responsibilities and Challenges
  
  Managing the design planning and the achievement of the Design/Verification reviews in all step of the Design.
• Delivering all TC&IS Engineering outputs including, Train Control and Monitoring System Requirements and Architecture, Software specification or Functional Design Description, Software, Electrical Schemes and Electrical Products definition (with the support of Electrical Lead Engineer), in compliance with the Engineering Quality, Cost and Delay commitments.
• Managing interface and ensure follow up of sub-systems (electrical components, PAPIS (Public Address and Passengers Information Systems), CCTV, Multimedia, TCMS, Event recorder, Train Ground Communication, ATC(Automatic Train Control)/Safety equipment).
• Ensuring standardization and maximize the carry over with previous project.
• Supporting Industrial and Manufacturing areas during First Train Assembly.
• Supporting Commissioning and Validation area during First Train tests.
• Ensuring that the cybersecurity requirements are properly managed on each project/program and follow-up the main open actions for "at risk" or challenging projects/programs.
• Functional management of the Train Control & IS resources of his/her project.
• Formulating a design solution that fulfils the specified customer requirements by defining the architecture and performances of the TC&IS subsystems and functional studies he/she is responsible for, maximizing the re-use of service-proven design patterns.
• Monitoring, control and consolidate the TC & IS work package (Work Package Review, Risk mitigation, Quality Cost & Delay project target) and ensure the reporting activities to the Project Engineering Manager of the project (PrEM).
• Defining the applicable TCMS configuration (low voltage scheme, apparatus, and software version) with the Train System Engineer, Train Design Engineer, Project Engineering Manager and its team.
• Contributing to the return of experiences on his/her domain (Software, Schematic, Apparatus).
• Contributing for technical specificities and expertise to advice the Project Team and/or Customer.
• Supporting the other stakeholders (design, sourcing, validation etc..) in the understanding of the Cybersecurity processes and actions in particular with regards to the interfaces in between the teams.
• Being the responsible at Project level for the transverse Cybersecurity actions and for topics addressed at: Project (progress plan), Region, Métier Manager level.

Qualifications

• Rolling stock functional engineer experiences on several train functions, >5 yrs.
• Work package and Team management experiences.
• Hands-on electrical and schematic design activity.
• Hands-on experience in design & development of model based control systems using application tools like DCUTerm, Control Build, Matlab / Simulink, Matrix or similar tools.
• Knowledge of network topologies and interfaces for Serial, Ethernet, MVB and other industrial communication network.
• Communication abilities.
• Innovation

Stay & Play Coming Your Way

Join the team at Aloft Singapore Novena by Marriott International!

WE ARE HIRING!

Who are we?

We aren’t your typical hotel – but we aren’t too cool for school, either. We love when Talents express their unique personalities and embrace a culture of open thinking, approachability, and flexibility. After all, the best and most fun ideas to enhance the guests’ stay come from sharing passions.

We’re looking for confident self-expressers who aren’t afraid to draw outside the lines. If you are someone who gets excited about the possibilities in connecting with others, then Aloft Singapore Novena is the place for you, where you'll be part of the largest Aloft Hotel in the world with a slew of employee benefits.

Be where you can do your best work,​ begin your purpose, belong to an amazing team, and become the best version of you.

Job Designation: Talent Development & Quality Executive

Job Description

Talent Development & Quality Officer/Executive

Function as primary support to the Talent Development & Quality team in maintaining the quality management system and learning programs to maximise guest experience and operating efficiency throughout the Hotels' operations. Various tools will be utilised, including learning management systems, quality audits, and 3rd party website reviews.

We regret that 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 holder is to work with PI and the research team to conduct Research Characterizing Airborne Pollutants in Urban Environment.

The research activities involve (but not limited to):

• Operating a wide variety of instruments, data retrieval
• Laboratory chemical analyses and speciation
• Modeling chemical reactions of airborne pollutants
• Assisting and contributing to project deliverables, including,
• Planning and conduct experiments, data analyses, progress reporting, report writing, etc.

Qualifications

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

• Fast learner capable of conducting independent research and proficient literature search, review & summary with strong background in chemical engineering / chemistry / physics
• Sufficient experiences in applying Pythons functions of matplotlib, and numPy, pandas, statsmodels, etc
• Modeling chemical reactions of airborne pollutants through implicit modules
• Experiences of applying machine learning to handle big data
• Experiences of laboratory chemical analyses using chromatography, such as GC-MS-MS, LC-MS-MS, etc
• Experiences of operating instruments measuring physical properties of aerosols
• Experiences in conducting field studies of aerosol and VOC sampling using various instruments
• 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 Research Assistant will work closely with the Principal Investigator on several research projects on using machine learning in chemical and control engineering problems
• The Research Assistant will help to develop machine learning models for both theory and applications in advanced control systems

Job Requirements

• A Bachelor degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science, Chemistry, etc.
• Experienced in machine learning, optimization and programming languages (e.g., python, Matlab, C++, etc)
• Any experience with 1) advanced control, 2) machine learning theory and applications, and 3) chemical engineering and chemistry is a plus

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

Sustainable Bio-platform for High Quality Microbial Protein Production. To perform experimental and simulation work on system integration sand life cycle assessment .

Job Requrements

Ph.D. degree in Chem. Eng. and related research areas.

Experience researcher in chemical, biomedical, and environmental engineering. System integration and LCA background will be desirable.