Total 51 systems engineer job vacancies in Education / Training category in Singapore

About the Role 

The Advanced Remanufacturing and Technology Centre (ARTC) is looking for a Lead / Senior Solution Architect to drive the design and implementation of enterprise-scale agentic AI systems for industrial and enterprise applications. This role focuses on architecting AI-enabled platforms and workflows that leverage LLMs, tool orchestration, autonomous agents, enterprise integrations, and scalable cloud-native systems to support intelligent operations and decision-making. You will work closely with engineering teams, AI researchers, and business stakeholders to shape technical strategy, define system architectures, and lead the delivery of production-grade AI solutions. We are looking for experienced architects who combine strong software engineering and system design capabilities with deep interest in emerging agentic AI technologies and practical enterprise adoption. 

Key Responsibilities

• Architect and lead development of enterprise-scale agentic AI systems and platforms 
• Design AI orchestration workflows involving LLMs, tools, agents, and enterprise integrations 
• Define scalable, secure, and reliable system architectures and engineering practices 
• Collaborate with stakeholders to translate operational needs into AI-enabled solutions 
• Evaluate and adopt emerging technologies related to agentic AI and enterprise AI systems 
• Provide technical leadership and mentorship to engineering teams 

Job Requirements

• Degree in Computer Science, Software Engineering, or related fields 
• Strong experience in software architecture, backend systems, or enterprise platform development 
• Experience designing scalable cloud-native or distributed systems 
• Familiarity with LLMs, AI application architectures, and orchestration frameworks 
• Interest or experience in agentic AI systems, automation workflows, or multi-agent applications 
• Strong communication, problem-solving, and stakeholder management skills 

Good to have 

• Experience with cloud platforms such as Azure, AWS, or GCP 
• Familiarity with Docker, Kubernetes, CI/CD pipelines, or MLOps practices 
• Experience building AI-enabled enterprise applications, copilots, or intelligent automation solutions 
• Exposure to AI governance, observability, or security considerations for AI systems 
• Experience working with manufacturing, industrial systems, or enterprise digital transformation initiatives 

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

• Develop and iterate on locomotion controllers and motion policies for a legged platform
• Train and evaluate policies in simulation across walking, recovery, stair climbing, and load-bearing behaviors
• Design reward functions, curriculum schedules, and training infrastructure for real-world robustness
• Drive systematic sim-to-real transfer and hardware iteration
• Integrate locomotion outputs with the broader autonomy stack
• Collect and analyze hardware telemetry to guide policy improvement

Requirements

• Strong foundations in reinforcement learning, optimal control, and rigid body dynamics
• Hands-on experience training or deploying locomotion and motion control policies on physical legged robots, gained through industry or research work
• Proficient in Python, with strong JAX or PyTorch experience
• Experience with physics simulation environments such as MuJoCo, Isaac Gym, Genesis, or equivalent
• Practical experience closing the sim-to-real gap on a real platform
• Candidates with limited industry experience are welcome to apply, provided this is supported by strong relevant academic or research work, such as a thesis, publications, or hands-on robotics projects

Tyson Jay Management Pte Ltd | EA License No.: 24C2479 

Ivan Lim | EA Personnel No.: R1109856

The Energy Research Institute @ NTU (ERI@N) conducts applied research in advanced energy systems and sustainable infrastructure. This position supports an ERI@N-led project on integrating non-conventional geothermal energy into data centre cooling in Singapore.

We are seeking a Research Fellow to lead the development of advanced modelling and design methodologies for integrated hydrogen-energy systems, with a focus on thermal integration of metal hydride storage systems.

The Research Fellow will develop CFD models, process simulations, and system-level integration strategies to enable efficient hydrogen desorption driven by waste heat. The role includes the design and optimisation of thermal management systems, supporting the development of scalable and deployable hydrogen solutions.

The research will directly contribute to the development of applied energy technologies with strong industrial relevance and near-term deployment potential.

Key Responsibilities

• Develop CFD models for thermal management and heat transfer within metal hydride storage systems, including internal heat exchanger design and thermal enhancement strategies.

• Design and optimise heat integration solutions for hydrogen desorption using waste heat from high-temperature systems.

• Develop process flow diagrams (PFDs) and system-level models for integrated hydrogen-energy systems.

• Perform multi-physics modelling (thermal, fluid, and mass transfer) of hydrogen storage and release processes.

• Support system architecture definition, thermal loop design, and control strategies for integrated systems.

• Conduct techno-economic and performance analysis of integrated hydrogen systems.

• Contribute to system integration, commissioning, and experimental validation activities.

• Collaborate with international industrial and academic partners in applied R&D projects.

• Prepare technical reports, scientific publications, and funding proposals.

• Support project management activities, including coordination, reporting, and stakeholder engagement.

• To develop and assess geothermal-driven cooling architectures through modelling, optimisation, and techno-economic analysis, supporting low-carbon cooling solutions for Singapore’s data centre sector.

Job Requirements

• PhD in Mechanical Engineering, Energy Engineering, Chemical Engineering, or related field.

• Strong expertise in CFD (ANSYS Fluent / OpenFOAM or equivalent) for heat transfer and fluid flow.

• Experience in thermal system design and heat integration, preferably involving high-temperature systems.

• Experience with hydrogen systems, metal hydrides, or gas-solid thermal processes is highly desirable.

• Experience in process modelling and simulation (e.g., Aspen, Modelica, MATLAB, Python).

• Strong understanding of heat exchangers, thermal loops, and multi-physics systems.

• Experience in techno-economic analysis and system optimisation.

• Familiarity with system integration and experimental validation is an advantage.

Additional Skills

• Ability to work in applied, industry-driven R&D environments.

• Experience in proposal writing and project management is highly desirable.

• Willingness to travel and work in international environments.

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

The School of Mechanical & Aerospace Engineering conducts research to enhance knowledge and drive innovation in urban mobility and to pave the way for Singapore's future land transport system. We are seeking to hire a Research Assistant / Associate to help in investigating the relationship between autonomous vehicles and path users on public paths. The role focuses on the design, development, and operation of experimental test rigs, including laboratory setups and field experiments.

Key Responsibilities:

• Experiment setup and testing

• Component assembly

• Sensors and hardware integration

• Data acquisition and analysis

Job Requirements:

• Education qualifications: B.Eng or M.Eng in Mechanical Engineering, Mechatronics, or related field.

• Good verbal and written communication skills, ability to work independently and in a team

• Proficient in mechanical experiment setup and testing, mechatronic systems integration involving sensors/actuators. Working knowledge of data acquisition and analysis, microcontrollers, and CAD tools is desirable.  

• Prior industrial or research experience in building experimental test rigs and mechatronics systems.

• Strong problem-solving ability, attention to details, and commitment to delivering high-quality research outputs.

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

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 a Research Fellow to support research and development activities in power electronics and energy systems. The role involves designing, developing, and testing advanced power electronic converters and control systems for applications such as renewable energy integration, energy storage, and smart grids. The Research Fellow will also contribute to research proposal preparation, project execution, and dissemination of research outcomes.

Key Responsibilities:

• Conduct research and development in power electronics converters, control, and energy systems.

• Design, simulate, and develop power electronic converter prototypes and associated control algorithms.

• Perform experimental testing, data analysis, and performance evaluation of power electronic systems.

• Develop simulation models using tools such as MATLAB/Simulink, PLECS, or PSCAD.

• Support the design, integration, and testing of laboratory prototypes and hardware setups.

• Contribute to research proposal preparation, including literature review, technical writing, and development of project ideas.

• Assist in technical reporting, documentation, and publication of research outcomes in journals and conferences.

• Collaborate with research team members, students, and industry partners.

• Support supervision of graduate students and research assistants when required.

• Ensure proper laboratory safety practices and equipment maintenance.

Job Requirements:

Qualifications

• PhD degree in Electrical Engineering, Power Electronics, or a related field.

• Strong background in power electronics, converter design, and control systems.

• Experience with simulation tools such as MATLAB/Simulink, PLECS, PSCAD, or equivalent.

• Experience in hardware prototyping, testing, and laboratory experimentation is preferred.

• Prior experience in research proposal writing or technical grant preparation is an advantage.

Competencies

• Strong analytical and problem-solving skills.

• Ability to work independently and collaboratively in a research environment.

• Good technical writing and communication skills.

• Ability to manage multiple research tasks and deadlines.

• Strong interest in renewable energy systems, power electronics, and sustainable energy technologies.

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

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 a Research Fellow to support research and development activities in power electronics and energy systems. The role involves designing, developing, and testing advanced power electronic converters and control systems for applications such as renewable energy integration, energy storage, and smart grids. The Research Fellow will also contribute to research proposal preparation, project execution, and dissemination of research outcomes.

Key Responsibilities:

• Conduct research and development in power electronics converters, control, and energy systems.

• Design, simulate, and develop power electronic converter prototypes and associated control algorithms.

• Perform experimental testing, data analysis, and performance evaluation of power electronic systems.

• Develop simulation models using tools such as MATLAB/Simulink, PLECS, or PSCAD.

• Support the design, integration, and testing of laboratory prototypes and hardware setups.

• Contribute to research proposal preparation, including literature review, technical writing, and development of project ideas.

• Assist in technical reporting, documentation, and publication of research outcomes in journals and conferences.

• Collaborate with research team members, students, and industry partners.

• Support supervision of graduate students and research assistants when required.

• Ensure proper laboratory safety practices and equipment maintenance.

Job Requirements:

Qualifications

• PhD degree in Electrical Engineering, Power Electronics, or a related field.

• Strong background in power electronics, converter design, and control systems.

• Experience with simulation tools such as MATLAB/Simulink, PLECS, PSCAD, or equivalent.

• Experience in hardware prototyping, testing, and laboratory experimentation is preferred.

• Prior experience in research proposal writing or technical grant preparation is an advantage.

Competencies

• Strong analytical and problem-solving skills.

• Ability to work independently and collaboratively in a research environment.

• Good technical writing and communication skills.

• Ability to manage multiple research tasks and deadlines.

• Strong interest in renewable energy systems, power electronics, and sustainable energy technologies.

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

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 1,000 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 seeking a Research Associate in Autonomous Systems and Control to develop efficient, performance-guaranteed distributed control methods leveraging cutting-edge learning algorithms and AI techniques. The Research Associate is expected to conduct high-quality research, publish in leading journals, and contribute to pedagogical innovation research aimed at improving the learning experience in the Modelling and Control course

Key Responsibilities: 

• Conduct advanced research in autonomous systems, learning-based control, and pedagogical innovation for Modelling and Control.

• Develop and implement novel distributed control strategies for networked cyber-physical systems.

• Publish high-quality research findings in leading international journals.

• Prepare reports and related documentation for pedagogical innovation projects aimed at enhancing the learning experience in Modelling and Control. 

Job Requirements: 

• Master degree in Electrical Engineering, Computer Science, Mechanical Engineering, or other related fields. 

• Solid Mathematical and Programming skills. 

• Strong expertise in control theory. 

• Strong publication track record.   

• Self-Motivated and takes initiative  

• Independent and can work well with a team  

• Ability to adapt to changing priorities 

• Good written and oral communication skills. 

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

Key Responsibilities

• Develop data-driven energy disaggregation models to estimate machine-, process-, and batch-level energy consumption from aggregated or limited metering data.
• Design and implement energy monitoring, analytics and benchmarking algorithms for energy performance tracking, anomaly detection, and causal analytics related to energy-saving of industrial equipment and manufacturing processes.
• Conduct experiments, model validation, and performance evaluation using industrial datasets.
• Work closely with project partners, engineers, and researchers to translate research outcomes into deployable industrial solutions.

Requirements

• Bachelor’s or Master’s degree in Electrical Engineering, Mechanical Engineering, Computer Science, Data Science, Industrial Engineering, or a related field.
• Strong programming skills in Python, with experience in data analytics, machine learning, and time-series processing.
• Knowledge of energy systems, power consumption analysis, industrial equipment, or manufacturing processes.
• Experience with machine learning techniques for regression, classification, anomaly detection, forecasting, or signal disaggregation.
• Ability to process and analyze large-scale time-series datasets.
• Good problem-solving skills and ability to work independently in applied research and development projects.
• Good written and verbal communication skills.

Preferred Qualifications

• Experience in non-intrusive load monitoring, energy disaggregation, virtual sensing, or industrial energy analytics.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with causal analytics.
• Knowledge of manufacturing systems, additive manufacturing, CNC, heat treatment, pumps, compressors, motors, or other industrial equipment.
• Prior experience in applied R&D projects with industry partners is an advantage.

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.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28Robotics%29/33299-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

•             Robot design.

The candidate is expected to assist in the design, fabrication, and testing of a novel robotic system based on application-related specifications.

•             Robot experiments.

The candidate is expected to support the definition of experimental protocols, in terms of trials and parameters to measure, to help with the experimental set-up, experimental validation, performance testing, and iterative improvements of developed prototypes and with the recording and analysis of experimental results.

•             Collaborate with cross-functional teams to integrate mechanical, electrical, and software components into functional robotic systems.

•             Support applied projects in collaboration with industrial partners and contribute to technology transfer efforts.

•             Present research findings at international workshops, conferences, and internal project meetings.

•             Contribute to the preparation of technical reports and assist in writing articles for publication in top-tier journals and conferences.

Qualifications

•             Mechanical Engineering degree

•             Robotics expertise: knowledge of robotics and soft robotics fundamentals, skills for robot design.

•             Research experience, even as a student, including skills for experimental research and paper preparation.

•             Hands-on experience in robotics, soft robotics, or interactive systems.

•             Proficiency in CAD software, prototyping, and mechatronics.

•             Ability to work collaboratively in a multidisciplinary team environment.

•             Strong problem-solving skills and creativity.

Job Title: AI Research Engineer - Vision-Language Action Models

Griffin Labs is looking for a Founding AI Research Engineer to lead the adaptation and deployment of Vision-Language-Action (VLA) models. We are focused on solving high-dexterity manipulation through cross-embodiment learning—training models that generalize across diverse robotic platforms and hardware configurations.

The Role

You will own the full development lifecycle of autonomous capabilities. This is an end-to- end mission: from reviewing raw trajectory data and designing model architectures to deployment and fleet-level monitoring. You aren’t just training models; you are building the systems that allow them to function in the real world.

Key Responsibilities:

• End-to-End Ownership: Lead the "data-to-deployment" loop—curating datasets, fine-tuning VLA models, and building the monitoring systems that ensure fleet-level reliability.

• Cross-Embodiment Learning: Develop and optimize models capable of handling diverse robot morphologies and kinematic constraints.

• Model Adaptation: Architect and fine-tune VLA stacks that bridge high-level reasoning with low-level whole-body control.
• Academic Collaboration: Work alongside expert research advisors from institutions like Stanford, NTU, and SUTD to push the boundaries of what's possible in robotics.

• Validation: Design robust evaluation metrics in Isaac Sim/MuJoCo and bridge the Sim2Real gap for a production fleet.

Requirements

• Technical Depth: A strong fundamental understanding of Transformers, Diffusion architectures, and LLMs/VLMs, particularly as they apply to sequential decision-making or action prediction.

• ML Expertise: Deep proficiency in PyTorch and experience fine-tuning large-scale multimodal models.

• Cross-Embodiment: A strong interest or background in generalizing AI across different robot types.

• Simulation: Fluency in environments like Isaac Sim or MuJoCo and the nuances of the "Reality Gap."

• Software Foundations: High proficiency in Python.

• Founding Mindset: High agency and the ability to build necessary tooling, scripts, and evaluation frameworks from scratch.

Why Griffin Labs?

We are a lean, technical team moving at the pace of frontier AI. As a founding hire, you will have a direct hand in shaping our technical North Star and defining how the next generation of robots learns from the world

Job Summary

About the Role

The Institute of High Performance Computing (IHPC), A*STAR, is seeking a highly motivated Research Engineer to develop and deploy advanced AI systems that translate cutting-edge research into scalable real-world applications.

The successful candidate will work closely with research scientists to implement, optimize, and operationalize AI models across healthcare and biomedical domains. This role combines software engineering, machine learning, and systems engineering to bridge the gap between research and deployment.

Key Responsibilities

AI System Development

• Design, develop, and maintain machine learning and deep learning systems.
• Implement state-of-the-art AI algorithms from research prototypes into production-quality software.
• Build scalable data processing and model training pipelines.
• Develop multimodal AI systems integrating text, image, video, sensor, and structured data.
• Optimize model training, inference, and deployment workflows.

Research Translation

• Collaborate with AI researchers to translate novel algorithms into robust software solutions.
• Reproduce and benchmark research models.
• Develop reusable AI frameworks, libraries, and tools.
• Support experimentation, model evaluation, and performance optimization.

Software & Infrastructure Engineering

• Design scalable cloud and on-premise AI infrastructure.
• Develop APIs, backend services, and model-serving platforms.
• Implement automated testing, monitoring, and CI/CD pipelines.
• Support large-scale distributed training and inference systems.

Deployment & Integration

• Deploy AI solutions into healthcare, scientific, and enterprise environments.
• Integrate AI systems with operational workflows and external platforms.
• Develop monitoring tools for model performance and reliability.
• Support technology transfer and production deployment activities.

Requirements

Essential

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, or related disciplines.
• Strong programming skills in Python.
• Experience with PyTorch, TensorFlow, or similar machine learning frameworks.
• Experience in software engineering best practices.
• Familiarity with Linux, Git, and software development workflows.
• Strong problem-solving and system design skills.

Preferred

• Experience with:Large Language ModelsMultimodal AIComputer VisionMLOps platformsCloud Computing (AWS, Azure, GCP)Containerization (Docker, Kubernetes)Distributed ComputingGPU Computing

What We Offer

• Opportunity to work on cutting-edge AI technologies with real-world impact.
• Access to world-class computational infrastructure and research facilities.
• Collaboration with leading researchers, clinicians, scientists, and industry partners.
• A dynamic environment supporting innovation, learning, and career growth.

We are looking for a research engineer to customize and make our ground penetrating radar market ready. The role will focus on the hardware side of the project which involves the miniaturization of the GPR, antenna fabrication and integration, product improvement and customization for the market.

Key Responsibilities:

• Ground penetrating radar miniaturization, customization and integration

• Improve the product performance and make the product more appealing to the market

• Interact and coordinate with industry and customers to provide a service

• Present the product and explain the product well

• Help to raise funds for a spin-off and do marketing for the product.

• Other administrative duties as required.

Job Requirements:

• Bachelor qualification degree in Electrical and Electronic Engineering or related field

• At least some of relevant experiences in similar role / technical hands-on experience in hardware integration

• Familiarity with funding system in Singapore

• Good written and oral communication skills

• Proficiency in hardware integration, system programming

• Competent in hands-on work, presentation and fund raising.

• Interpersonal skill such as develop solutions under strict timelines, meticulous and eye for details / excellent organizational / time management skills.

• Entry level candidates are welcome to apply

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

About Fragment Works and Moment AI

FRAGMENT WORKS PTE. LTD. is a Singapore-incorporated technology company operating the Moment AI platform at https://momentvideo.ai/.

Moment AI is a leading VC-backed video AI foundation model company developing advanced video AI technologies and business-to-business infrastructure for enterprise customers. The company focuses on building scalable, production-grade video AI systems that support real-world commercial applications across video generation, video understanding, model deployment, and model-sales operations.

Through API-based capabilities, Moment AI serves companies in the short-video, creator economy, advertising, media, and AI application sectors. Its platform is designed to help enterprises integrate video AI into their products and workflows efficiently, enabling automated content creation, intelligent video analysis, and next-generation AI-powered media experiences.

Moment AI is founded by a team of video industry veterans with deep operational and technical experience in scaling short-video platforms to millions of users. The founding team brings together battle-tested entrepreneurs, infrastructure builders, and AI researchers with hands-on experience across video platforms, creator ecosystems, high-concurrency video infrastructure, and multimodal AI.

About the Role

We are building our own foundation model for video generation, based on DiT and Flow Matching architectures. We are looking for a Training Infrastructure Engineer who can turn cutting-edge research code into a stable, scalable, and high-throughput training system running on large-scale GPU clusters.

This role is ideal for an engineer who enjoys solving deep systems problems at the intersection of distributed training, CUDA performance, video data pipelines, model training stability, and large-scale ML infrastructure. You will work closely with researchers and platform engineers to ensure that our video generation training stack can reliably produce results at the thousand-GPU scale.

Key Responsibilities

• You will design, optimise, and maintain large-scale distributed training systems for video generation foundation models. This includes implementing and improving training strategies such as FSDP, tensor parallelism, context parallelism, and Ulysses-style sequence parallelism, with a strong focus on improving throughput, scaling efficiency, and MFU.
• You will build and optimise PB-scale video data pipelines, including NVDEC-based video decoding, VAE latent caching, variable-resolution bucket sampling, and efficient data loading for high-throughput model training.
• You will work on memory and performance optimisation across the training stack, including FlashAttention,FP8 mixed precision, Triton kernels, CUDA-aware profiling, activation check pointing strategies, and communication-computation overlap.
• You will also be responsible for training stability and reliability. This includes identifying the root causes of loss spikes, divergence, slow nodes, communication bottlenecks, check point failures, and data-related instability, as well as designing mechanisms for fast checkpoint recovery and automatic exclusion of problematic nodes.

Requirements

• The ideal candidate has strong hands-on experience with PyTorch distributed training and a solid understanding of CUDA architecture, GPU memory hierarchy, NCCL communication, and performance profiling.
• You should have source-level familiarity with at least one major large-scale training framework, such as Megatron-LM, DeepSpeed, PyTorch FSDP, or TorchTitan, and be comfortable reading, modifying, and debugging framework internals.
• You should have at least one year of practical experience training models on large GPU clusters of 256 GPUs or more, with proven experience in debugging distributed training failures and improving system-level training efficiency.
• Strong candidates will be able to reason across the full training stack, from data ingestion and model parallelism to kernel-level optimisation and fault-tolerant training operations.

Preferred Qualifications

• Experience with DiT, diffusion models, Flow Matching, or video generation models would be highly advantageous.
• Experience processing large-scale video datasets, building video decoding pipelines, or working with VAE latent caching systems would be a strong plus.
• Hands-on experience writing or optimising Triton, CUDA, or CUTLASS kernels would be valuable.
• Familiarity with open-source video generation projects such as HunyuanVideo, Wan, CogVideoX, or similar systems at source-code level would also be beneficial.

What We Offer

You will work with real large-scale compute resources, including access to thousand-GPU-level training infrastructure. You will join a team that treats large-scale model training as a rigorous engineering discipline, not just a research experiment.

We provide an environment where engineers can work on technically meaningful infrastructure problems, collaborate closely with frontier model researchers, and contribute to open-source or publication work where appropriate and within applicable compliance boundaries.

Employment Practices

We are committed to fair and merit-based hiring. All candidates will be assessed based on job-related skills, experience, and ability to perform the role. We welcome applications from qualified candidates and do not discriminate on the basis of age, race, gender, religion, marital status, family responsibilities, disability, or other non-job-related characteristics.

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-%28Maritime-Decarbonization-Quantitative-Analysis%2C-Systems-&-Policy-Modelling%29/32712-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Centre for Maritime Studies (CMS) and Department of Industrial Systems Engineering and Management at the National University of Singapore (NUS) invite applications for the position of Research Fellow to support maritime decarbonization research, focused on the IMO Net-Zero Framework (NZF) and related regulatory and market developments. The role involves quantitative analysis, scenario & optimization modelling, and data-driven assessment of compliance pathways, fuel transition, and strategic implications for shipping and maritime ecosystem.

Key Responsibilities

• Conduct quantitative and scenario-based analysis of maritime decarbonization pathways, compliance strategies, and regulatory impacts.
• Develop analytical and modelling frameworks to assess compliance costs, fuel/fleet transition and technology adoption.
• Analyze maritime datasets (e.g., AIS, fleet and vessel data) to support empirical and policy-relevant assessment.
• Contribute to reports, publications, presentations, and stakeholder-oriented outputs.

Qualifications

• PhD in Industrial Engineering, Operations Research, Maritime Studies, Energy Systems, or a related quantitative discipline.
• Background in maritime decarbonization, quantitative analysis, optimization/ML modelling, uncertainty/scenario analysis.
• Proficiency in programming (Python/MATLAB/R/Excel) for data analysis and modelling.
• Familiarity with maritime datasets (e.g., AIS, SeaWeb, IHS) and maritime regulatory developments is an advantage.
• Strong publication record, analytical skills, and ability to communicate with both academic and policy audiences.

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-EngineerAssistant-%28Interdisciplinary%29%2C-ChBE/33229-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Positions are available for Research Engineers, Research Assistants, and Ph.D. students in the research group of Prof. Soh Siow Ling, at the Department of Chemical and Biomolecular Engineering, National University of Singapore (NUS).  

The group’s general program of research involves the coupling of organic materials, mechanical forces, and electrostatics at different interfaces (e.g., solid, liquid, or gas). This coupling is currently greatly under-explored and poorly understood in science. At the same time, the coupling gives rise to many fascinating new natural phenomena for exciting fundamental discoveries and development of impactful and original technologies. 

The general approach of the group is to conduct original programs and new directions of research with strong fundamental science. The group is highly interdisciplinary and involves engineering (e.g., fluid mechanics), materials science, chemistry, and physics. Different organic materials are used, including polymers (e.g., stimuli-responsive polymers), hydrogels, and covalent organic frameworks (COFs). 

One project involves an original system that harvests water energy from nature (e.g., rain and rivers) and directly generates electricity by solid-liquid charge separation with high energy conversion efficiency. Other projects involve clearing virus-laden atmospheric aerosols and preventing the spread of infectious diseases (e.g., COVID-19) and development of clean surfaces that do not adhere any dust on them. Another research involves stimuli-responsive polymers for small molecular separation, smart delivery, and intelligent soft machines.

A recent exciting and emerging field from our group is the development of novel mechanocatalysts for performing mechanochemical reactions with high energy conversion efficiency. Harvesting energy from mechanical forces of nature (e.g., wind or water flows) is a novel and sustainable approach to performing chemical reactions. 

Qualifications

The ideal candidate is preferably someone open-minded to conducting original fields of research, independent, and hardworking. Because the research of the group is highly interdisciplinary and many projects in different disciplines are ongoing, candidates with a Bachelor’s degree from a wide range of backgrounds will be considered for different projects, including engineering (e.g., chemical, mechanical, etc), materials science, chemistry, and physics.  

For more information on the background of the research, please refer to: https://blog.nus.edu.sg/chessl/