Total 500 Education / Training job vacancies in george town

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-Assistant%2C-AIDF/33495-en_GB/?st=4993B7046BEEBA984DA71E08B1EF737E0DBC9DA2

We regret that only shortlisted candidates will be notified.

Role Overview

We are looking for a motivated Research Assistant to support AIDF’s digital marketing, and programme outreach activities.

Key Responsibilities

Digital Marketing and Campaign Support

• Support the planning and execution of digital marketing campaigns across multiple platforms, including social media, email, website, and digital advertising channels.
• Assist in creating, scheduling, and publishing content for LinkedIn, website updates, newsletters, and other digital channels.
• Support campaign tracking, performance reporting, and basic analytics to evaluate campaign effectiveness.
• Coordinate with internal teams, faculty, partners, vendors, and designers to prepare marketing materials and campaign assets.
• Help maintain a consistent brand voice and professional image across AIDF’s digital channels.

Social Media and Content Support

• Manage day-to-day social media content posting and engagement, particularly on LinkedIn and other relevant platforms.
• Draft and refine social media posts, event highlights, programme announcements, and partner engagement content.
• Support content collection from events, programmes, faculty, students, alumni, and industry partners.
• Assist in developing simple visual assets, captions, short write-ups, and promotional materials.
• Support regular website updates, including programme information, event pages, news articles, faculty profiles, partner updates, and other content.
• Ensure website content is accurate, current, and aligned with AIDF’s branding and communication standards.

Academic and Programme Operations Support

• Provide administrative and operational support for academic programmes, workshops, seminars, and events when required.
• Assist with programme marketing, participant communications, registration tracking, logistics coordination, and post-event follow-up.
• Support the preparation of programme materials, reports, attendance records, feedback forms, and certificates where applicable.

Qualifications

• Degree in Marketing, Communications, Business, Media, or a related discipline.
• 1 to 2 years of relevant experience in digital marketing, social media marketing, content coordination, or communications.
• Good writing skills and the ability to draft clear, professional, and engaging content.
• Familiarity with social media platforms, especially LinkedIn.
• Basic experience with website content management systems would be an advantage.
• Basic understanding of email marketing, digital campaigns, or campaign analytics would be useful.
• Comfortable handling multiple tasks across marketing, communications, and programme support.
• Detail-oriented, organized, and able to follow through on operational tasks.
• Good interpersonal skills and the ability to work with faculty, colleagues, students, vendors, and external partners.
• Interest in fintech, AI, digital finance, or higher education would be an advantage.

Preferred Skills

Experience using tools such as Canva, LinkedIn, Mailchimp, WordPress, Google Analytics, or similar platforms.

Ability to support simple design work, content formatting, and digital asset preparation.

Prior experience in an education, research, technology, fintech, or professional services environment would be helpful.

Comfortable supporting events, workshops, and academic programme logistics.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28SHINE-Industry-Projects-and-Programme-Support%29/33489-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

SHINE Industry Projects and Programme Support
•             Coordinate SHINE consortium activities and industry project administration.
•             Support coordination among researchers, industry partners, government agencies, and internal stakeholders to facilitate SHINE activities and industry collaborations.
•             Coordinate industry project activities, including tracking project progress, deliverables, milestones, and reporting requirements.
•             Maintain project documentation, records, and administrative materials to support project execution and compliance requirements.
•             Support technical workshops, industry engagements, consortium activities, and collaborative initiatives involving SHINE researchers and industry partners.
•             Organise workshops, seminars, technical talks, industry visits, and stakeholder engagement activities.
•             Support development of postgraduate programme operations and related programme initiatives.
•             Liaise with researchers, industry partners, government agencies, students, and internal stakeholders to support programme objectives.
•             Provide administrative and operational support for SHINE initiatives and other ad-hoc programme activities as assigned.

Qualifications

•            Possess a Bachelor's degree in a STEM discipline (Science, Technology, Engineering or Mathematics), preferably in Electrical Engineering, Computer Engineering, Materials Science, Physics, Mechanical Engineering, or a related field.
•             Relevant experience in project coordination, industry collaborations, stakeholder engagement, programme administration, research administration, or related functions would be advantageous.
•             Experience coordinating projects, workshops, industry engagements, postgraduate programmes, internships, or multi-stakeholder initiatives would be advantageous.
•             Ability to engage effectively with researchers, students, industry partners, government agencies, and other stakeholders.
•             Strong interpersonal, communication, stakeholder management, and organisational skills.
•             Ability to manage multiple priorities and work effectively in a dynamic environment.
•             Experience in a university, research institute, government agency, corporate laboratory, or technology-related environment would be advantageous.
•             Familiarity with semiconductor technologies, advanced packaging, microelectronics, photonics, or related technology domains would be advantageous.
•             Self-motivated, resourceful, and able to work independently as well as collaboratively within a team.
•             Open to appointment on a fixed-term contract.

Teacher of Secondary Mathematics

An outstanding and inspirational Mathematics Teacher is required for August 2026. The right candidate will be an experienced Mathematics specialist able to teach the full age and ability range. Experience of teaching IGCSE (our three-year programme starts in Year 9) and the IB Diploma SL/HL is essential. Candidates with IB Diploma experience are particularly welcome to apply.

The successful candidate will be passionate about driving high quality teaching and learning in an inclusive school and committed to making a difference to the lives of the young people in their care. They will be a reflective practitioner and an effective collaborator, relentless in the pursuit of ‘better’ practice. Staff contribute to our pastoral care and well-being programme and to our co-curricular programme, making a full contribution to our vibrant community. Please see the job description and provide a letter of application and curriculum vitae.

We are an inclusive international school committed to ‘success for all’, offering diverse programmes to meet the needs of our learners.

The successful candidate will be passionate about learning and committed to making a difference to the lives of the young people in their care. They will be a reflective practitioner and an effective collaborator, relentless in the pursuit of ‘better’ practice. We are a school with a strong sense of community amongst staff and students. Staff contribute to our pastoral care and well-being programme and to our co-curricular programme, making a full contribution to our vibrant community.

Safeguarding

At Nord Anglia Education we are committed to providing a world class, safe, happy environment in which children and young people are able to thrive and learn. We are committed to safeguarding and promoting the welfare of all our students irrespective of race, ability, religion, gender or culture.

All post holders in regulated activity (having regular unsupervised contact with children) are subject to appropriate national and international vetting procedures including satisfactory criminal record checks from both your country of residence/birth and any country of residence within the last 10 years.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28SHINE-Programme-Management-and-Operations%29/33488-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

SHINE Programme Management and Operations 
•             Support the coordination and execution of SHINE research programmes in close collaboration with the Programme Director, principal investigators, researchers, and stakeholders.
•             Monitor programme deliverables, milestones, KPIs, and reporting timelines across SHINE projects and research thrusts.
•             Support coordination across SHINE research thrusts and facilitate interactions among principal investigators, researchers, industry partners, and funding stakeholders.
•             Coordinate and consolidate programme reports, including mid-term reviews, annual reports, final reports, presentations, and programme updates.
•             Support budget monitoring, grant utilisation tracking, expenditure reporting, fund requisitions, and budget virement processes.
•             Coordinate Governing Board (GB), Scientific and Technical Advisory Committee (STAC), programme review meetings, and related stakeholder engagements.
•             Assist in the preparation of technical and programme review materials, presentations, and supporting documentation.
•             Liaise with principal investigators, researchers, industry partners, and funding agencies to support programme execution and ensure timely delivery of project objectives.
•             Coordinate technical visits, industry engagements, and programme-related activities to support alignment between research activities and industry needs.
•             Maintain programme documentation, fixed asset records, compliance materials, and operational records.
•             Provide operational and administrative support for SHINE programme activities and initiatives as assigned.

Qualifications

 •            Possess a Bachelor's degree in a STEM discipline (Science, Technology, Engineering or Mathematics), preferably in Electrical Engineering, Computer Engineering, Materials Science, Physics, Mechanical Engineering, or a related field.
•             Relevant experience in research programme management, project coordination, industry collaborations, technology development programmes, research administration, or related functions would be advantageous.
•             Experience coordinating research projects, collaborative programmes, technical workshops, industry engagements, or multi-stakeholder initiatives.
•             Ability to engage effectively with principal investigators, researchers, students, industry partners, government agencies, and other stakeholders.
•             Strong interpersonal, communication, stakeholder management, and organisational skills.
•             Strong analytical and problem-solving abilities, with the capacity to manage multiple priorities and workstreams concurrently.
•             Familiarity with semiconductor technologies, advanced packaging, microelectronics, photonics, or related technology domains would be advantageous.
•             Experience in a university, research institute, government agency, corporate laboratory, or technology-related environment would be advantageous.
•             Proficient in Microsoft Office applications and comfortable working with project management and administrative systems.
•             Self-motivated, resourceful, and able to work independently in a dynamic research environment.
•             A collaborative team player with a positive attitude and strong attention to detail.
•             Open to appointment on a fixed-term contract

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28Membranes%29%2C-ChBE/33499-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

•    Design and synthesize chiral covalent organic frameworks (COFs);
•    Fabricate chiral COF membranes;
•    Evaluate membranes for chiral separations.

Job Requirements

•    Experience in organic synthesis, especially chiral synthesis;
•    Experience in porous materials and polymers;
•    Experience in membrane science and engineering.

About Cynapse 

Cynapse is a leading Agentic AI software company specializing in enterprise-grade Video Intelligence Solutions Powered by Agentic AI, tailored to meet the unique challenges of various industries. Our vertical-specific solutions empower organizations to enhance safety, operational efficiency, and security in complex environments such as roads, seaports, airports, and cities. 

Led by a global team with a proven track record of scaling startups into market leaders, we foster innovation, collaboration, and diverse perspectives. Headquartered from US, Cynapse serves clients worldwide, redefining what’s possible with video intelligence. 

Job Description 

We are looking for a Junior to Mid-Level Machine Learning Engineer to join our Model Engineering Team. This role is intended for engineers who view models as systems to be understood, developed, and improved rather than simply consumed as black-box components.

You will contribute across the full model lifecycle, from dataset preparation and architecture development to training, evaluation, and optimisation. Working closely with experienced engineers, you will improve model performance through experimentation, data-centric approaches, and systematic analysis, helping to build robust and efficient computer vision systems for real-world applications.

What You’ll Do: 

• Train, fine-tune, and evaluate computer vision models for tasks such as classification, object detection, segmentation, pose estimation, and action recognition.
• Contribute to model development through architecture enhancements, custom heads, loss functions, and training strategy optimisation.
• Design and execute experiments to evaluate model improvements and performance trade-offs.
• Prototype, benchmark, and assess new architectures, techniques, and approaches against established baselines.
• Investigate edge cases and performance limitations, and improve model accuracy, robustness, and efficiency.
• Consider practical constraints such as latency, throughput, resource efficiency, and hardware-specific optimisation.
• Collaborate with engineering teams to improve dataset quality, model performance, and system reliability.

Requirements 

• Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
• At least 2 years of hands-on experience training, fine-tuning, and evaluating computer vision models through academic, project, internship, or professional work.
• Hands-on experience with PyTorch and/or TensorFlow.
• Proficiency in Python and familiarity with Linux environments and command-line tools.

Bonus Skills 

• Experience modifying models beyond high-level APIs (e.g. custom heads, backbone modifications, loss functions, or training pipelines).
• Exposure to multimodal, vision-language, foundation, or open-vocabulary models.
• Experience with optimisation techniques such as quantisation, pruning, distillation.
• Familiarity with experiment tracking, reproducibility, or MLOps practices.

Personal Competencies 

• Strong interest in understanding how model architectures, data quality, and training strategies influence performance.
• Enjoy experimentation, performance analysis, and iterative model improvement.
• Eager to take ownership of model components and grow into increasingly complex model development responsibilities.

Note: Due to the nature of the role, the position is considered only for candidates who are already based in Singapore.

Project Overview

This project aims to develop a real-time blood analysis and diagnostic platform using an integrated microfluidic chip. This platform uses precision microfluidic technology to process and profile the biological activity of white blood cells which is related to a host of inflammatory conditions ranging from diabetes, sepsis to leukemia. The platform developed will enable point-of-care diagnosis of diseases and this project will accelerate the platform from bench to bedside through the development, deployment and testing of clinical samples.

This Engineering position offers a rare opportunity to bridge the gap between laboratory discovery of new technologies and real-world implementation of clinical deployment and testing. 

Responsibilities

The engineer is responsible for the design, prototype, manufacturing and testing of the medical device. This involves the use of with computer-aided design prototyping, setting specifications and assembly of mechnical/electrical components, testing and deployment of device for field testing.

Responsibilties include:

- To work closely with a team of clinical, mechanical/software engineers and data scientist for the medical device design and prototyping. Gather feedbacks on prototype designs by end-users.

- To Validate designs by analysing data gathered from component or system level testing. Use benchmarking techniques to characterise component and device performance.

- To ensure proper documentation of design history files and standardization of data storage for reports, presentations, technical and administrative documents.

- To source for vendors and components to ensure manufacturability and cost of medical device.

- To support the team for maintenance of equipment, inventory and purchases.

Requirements

- Bachelors/Masters in Mechanical, Electrical, Biomedical Engineering with at least 1 years of experience in hardware prototyping and/or microfluidic operations.

- Rapid prototyping experience in areas such as 3D printing, laser cutting, CNC, injection molding, microcontroller/microprocessor programming and relevant skills in embedded system.

- Prefered experience in commercial manufacturing, R&D project management and hardware testing/certification.

- Excellent debugging skills and strong ability to root cause, isolate and solve software/hardware system issues.

- Fluent in C++, Python (3.X) and relavent coding languages for software-hardware integration.

- A desire to deliver a quality and innovative medical diagnostic product that improves many people’s lives.

- Good communication and managing skills are important to work with colleagues efficiently in addition to creativity to solve problems and find improvements on products and processes already in place.

- Required experience and knowlegde to read or write scientific publications, patent search, schematics and data sheets for hardware components.

- Able and commited to work in Singapore. Willing to commute and meet regularly with vendors and collaborators at NUS, NUH, and partnering hospitals.

- Strong documentation and writing skills

- A desire to deliver a quality and innovative medical diagnostic product that improves many people’s lives.

Relevant Skills

2D/3D Computer Aided Designs, C++, Python, Operating CNC/3D printers, basic use of machine tools, electronics circuit design, Github 

To apply, please visit our website at: https://portal.smart.mit.edu/careers/career-opportunities

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.

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/ManagerAssistant-Senior-Manager-%28Experiential-Learning%29%2C-MBA-Programmes-Office/33498-en_GB/

We regret that only shortlisted candidates will be notified.

About NUS Business School

Founded in the same year that Singapore gained independence, NUS Business School stands today among the world’s leading business schools. It is distinctive for offering the best of global business knowledge with deep Asian insights, preparing students to lead Asian businesses to international success and to help global businesses succeed in Asia.

For more than 50 years, NUS Business School has offered a rigorous, relevant and rewarding business education to outstanding students from across the world. That would not have been possible without a group of dedicated professionals who are passionate about building a positive environment to grow and groom future business leaders. And we are looking to add to our BIZ family!

To learn more about the NUS Business School, please visit https://bschool.nus.edu.sg/

Job Description

The Manager/Assistant Senior Manager plays a key role in managing experiential learning courses within the MBA curriculum, including Launch Your Transformation and the MBA Consulting Project, while driving corporate outreach to source high-quality, real-world projects for students. This position focuses on building strong relationships with industry partners, collaborating with faculty and internal stakeholders, and ensuring that experiential learning courses and initiatives provide high-quality, relevant, and career-enhancing learning experiences aligned with the MBA programme’s objectives.

1. Corporate Outreach & Project Sourcing

• Identify and secure MBA Consulting Projects aligned to student’s learning objectives
• Build and maintain strong industry relationships to support consulting projects, MBA Clubs, and other experiential learning initiatives
• Explore potential collaborations with corporate partners for student engagement

2. Course Management

MBA Consulting Project

• Manage the MBA Consulting Project lifecycle from sourcing to completion
• Define project scope with project sponsors, deliverables, and expectations with companies
• Oversee student applications, team assignments, project supervision, and milestone tracking
• Facilitate briefings and align expectations among companies, supervisors, and student teams
• Monitor project progress, address challenges, and ensure timely delivery of outcomes

Other MBA Experiential Learning Course Management

• Manage end-to-end experiential learning course management that include courses planning and offerings, student’s enrolment and grading
• Liaise with teaching faculty on teaching requirements and planning
• Liaise with cross-faculty on course(s) offerings

3. Inter-School & Faculty Collaborations

• Manage and maintain relationships with cross-faculty collaborations on course offerings
• Identify potential partnership opportunities within the NUS ecosystem

4. Stakeholder Engagement & Performance Monitoring

• Serve as primary contact for student and corporate partner queries
• Support student performance and learning outcomes through guidance and feedback
• Measure project impact and stakeholder satisfaction; identify areas for improvement and implement enhancements

Additional scope for the Assistant Senior Manager grade: The incumbent will take on strategic leadership in continuously reviewing, designing, and expanding experiential learning opportunities and initiatives that enhance the MBA student learning experience, and will contribute to longer-term programme strategy and team succession planning.

Others

• Continuously explore possible process improvement, automation initiatives, and other functional areas as needed
• Assist in ad-hoc projects and initiatives assigned by the Head of Experiential Learning
• Provide support to the team in other functions when needed

Qualifications

• Bachelor’s Degree from a recognised university
• At least 5 years’ relevant experience in outreach, business development, stakeholder engagement, or a related field; candidates for the Assistant Senior Manager grade should have at least 8 years’ relevant experience, including some experience in programme design or team leadership
• Strong track record in corporate engagement and relationship management
• Experience in education, training needs analysis, or experiential learning is preferred
• Able to work independently, manage multiple priorities, and collaborate across teams
• Confident engaging with senior executives, faculty, and a diverse student body
• Excellent communication, interpersonal, and problem-solving skills
• A proactive self-starter who is resourceful, adaptable, and a fast learner in a dynamic, fast-paced environment
• Familiar with social media platforms (Facebook, Instagram, LinkedIn)
• Proficient in Microsoft Office (Word, Excel, PowerPoint, Outlook) and educational IT systems

(Appointment job grade will commensurate with the selected candidate's experience)

Project Overview

This project aims to develop and clinically validate a real-time blood analysis and diagnostic platform using an integrated microfluidic medical device. The platform uses precision microfluidic technology to process and profile the biological activity of white blood cells, which is related to inflammatory conditions ranging from diabetes and sepsis to leukemia.

The Postdoctoral Research Associate - Data Scientist will lead the acquisition, preprocessing, analysis, and modelling of medical device-generated data, and will work closely with clinicians, scientists, and engineers to translate AI/machine learning models into working, deployable software for clinical testing and point-of-care use.

This role offers a rare opportunity to bridge clinical data science, medical device engineering, and translational research, moving from experimental and clinical sample data to robust AI-enabled diagnostic workflows and deployable prototypes.

Responsibilities

The Postdoctoral Research Associate - Data Scientist is responsible for developing end-to-end data and AI/ML workflows for the medical diagnostic platform, from device data acquisition and signal/data preprocessing to model optimisation, validation, software integration, and deployment.

Responsibilities include:

- Work closely with clinicians, scientists, software engineers, mechanical/electrical engineers, and data scientists to define clinical use cases, data requirements, model outputs, and deployment workflows for the medical device platform.

- Design and implement reliable data acquisition pipelines from medical device hardware, sensors, imaging or signal outputs, and associated experimental or clinical metadata.

- Develop preprocessing, quality-control, annotation, feature-engineering, and data-management workflows for noisy, multimodal, longitudinal, or time-series biomedical data.

- Analyse experimental and clinical sample data to characterise device and biological performance, identify artefacts, benchmark platform performance, and support evidence generation for translational studies.

- Develop, train, validate, and optimise machine learning, deep learning, statistical, or hybrid models for diagnostic, predictive, or decision-support tasks using appropriate metrics, cross-validation, robustness checks, and uncertainty analyses.

- Translate research models into reproducible and deployable software components, including model inference pipelines, APIs, dashboards, reports, or lightweight user interfaces for clinical and laboratory testing.

- Support software-hardware integration for data acquisition, model inference, device feedback, and prototype deployment; assist with basic UX refinement based on clinician and end-user feedback.

- Maintain high-quality documentation of datasets, code repositories, model versions, experimental protocols, validation results, data dictionaries, and technical reports.

- Prepare manuscripts, presentations, grant reports, and invention disclosures; contribute to literature reviews, patent/IP searches, and responsible research dissemination where relevant.

- Support clinical study workflows by coordinating with clinical collaborators and applying good data governance practices for sensitive clinical and experimental data.

Requirements

- Ph.D. in Data Science, Computer Science, Artificial Intelligence/Machine Learning, Biomedical Engineering, Electrical Engineering, Bioinformatics, Statistics, Applied Mathematics, Computational Biology, or a related field. Candidates close to completion may be considered if the degree will be conferred before appointment.

- Demonstrated research experience in data science, machine learning, deep learning, signal/image processing, biomedical data analysis, time-series analysis, clinical AI, or related computational research.

- Strong programming skills in Python; experience with common scientific and ML frameworks such as NumPy, pandas, scikit-learn, PyTorch or TensorFlow, Jupyter, and Git/GitHub.

- Experience with data acquisition, data cleaning, feature engineering, model optimisation, evaluation, reproducibility, version control, and scientific software development.

- Familiarity with clinical or biomedical datasets, medical device data, biosensor/microfluidic data, imaging data, physiological signals, or multimodal data integration is highly advantageous.

- Experience translating ML models into usable software prototypes, such as REST APIs, dashboards.

- Working knowledge of software-hardware interfacing, instrument-control software, serial/USB/Bluetooth communication, microcontrollers, embedded systems, or edge AI deployment would be advantageous.

- Ability to work closely with clinicians and multidisciplinary teams to interpret findings, gather end-user feedback, define clinical workflow needs, and improve the usability of AI/ML outputs.

- Strong written and oral communication skills, including the ability to write scientific manuscripts, technical documentation, reports, research proposals, and presentations for technical and non-technical audiences.

- Strong commitment to robust, ethical, and responsible AI/ML development, including attention to data privacy, model bias, interpretability, clinical validity, reproducibility, and safe deployment.

- Able and committed to work in Singapore, and willing to meet regularly with collaborators at NUS, NUH, and partnering hospitals.

Relevant Skills

Python, R/MATLAB, SQL, NumPy, pandas, scikit-learn, PyTorch/TensorFlow, Jupyter, data acquisition, biomedical signal processing, time-series analysis, image processing/computer vision, data preprocessing, feature engineering, model validation, model optimisation, uncertainty/robustness analysis, explainable AI, data visualisation, dashboards, REST APIs, Docker, Linux, Git/GitHub, MLOps, UX prototyping, software-hardware interfacing, and clinical data governance.

To apply, please visit our website at: https://portal.smart.mit.edu/careers/career-opportunities

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.

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-Assistant-%28Designing-for-Relational-Safety-in-Children's-Online-Peer-Interactions%29%2C-DID/33492-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are hiring a Research Assistant to contribute to a project focused on Designing for Relational Safety in Children's Online Peer Interactions. The project aims to understand, design, and evaluate sociotechnical supports that help tweens navigate the complexities of online peer interactions. A core concern is how children can protect themselves while preserving their relationships. Within this overarching theme, we offer intellectual flexibility in defining specific research inquiries and design directions based on the researcher's expertise and interests.

The successful candidate will contribute across the research trajectory, from qualitative grounding (e.g., conducting interviews with stakeholders such as teachers and parents, and running co-design sessions with children) to translating these insights into tween-centered interactive prototypes. The researcher is expected to disseminate findings through high-impact publications in top-tier HCI venues.

Qualifications

Minimum Qualifications:
•    A BS or MS in HCI, Design, Information Science, Computer Science (Human-centered), or a closely related field.
•    Research experience in HCI, preferably with exposure to academic publication or conference venues (e.g., CHI, CSCW, ASSETS or DIS).
•    Proficiency in qualitative and/or mixed-methods research, including experience in co-design ethnographic studies, etc.
 
Preferred Qualifications:
•    Experience working with children as study participants.
•    Experience in system prototyping, with the ability to translate conceptual design requirements into functional artifacts.
•    Technical expertise in integrating AI/ML features into user-facing systems.

Job Description

The Genome Institute of Singapore (GIS) is the national flagship for genomic sciences, driving cutting-edge research at the intersection of biology, engineering, and medicine. This position is offered in the Laboratory of AI in Genomics, led by Prof. Mile Šikić, which uses advanced bioinformatics and deep learning approaches to develop next-generation models for genomic data analysis. We are group a of computer scientist with a mission to improve healthcare using advance deep learning models. Located in the heart of Singapore’s thriving biomedical hub, GIS offers a dynamic and collaborative environment, with close ties to world-class universities (NUS and NTU), pharmaceutical companies, and biotech start-ups. Joining our team means working on transformative projects with real-world impact, while benefiting from Singapore’s vibrant research ecosystem and strong support for innovation.

Project background:

De novo genome assembly has been one of the most challenging problems in genomics. However, with development of new long read sequencing technologies, new assemblers and manually curated high quality benchmarks including CHM13, HG002 and I002C assembling most of human chromosomes T2T has become a routine task.

This project will focus on a more challenging task, assembling of human cancer genomes which are especially difficult due to cancer genome heterogeneity. Using the fact that we can reconstruct normal tissue genomes routinely we aim to reconstruct cancer genomes.

Job duties and responsibilities:

We invite brilliant minds in computer science to join us at the cutting-edge of cancer genomics research, harnessing the power of artificial intelligence or classical algorithms. Your job will involve either the development of new algorithms or deep learning models focusing on understanding cancer genomes. The focus will be on de novo genome assembly methods for reconstructing cancer genomes or developing new generative RNA/DNA/epigenome/epitranscriptome foundation models and agents aiming to speed up therapeutics development.

The duties include development of AI models or algorithms.

Job Requirements:

• Bachelor or Master in Computer Science, Mathematics or Physics
• Experienced in deep learning or classical algorithms
• Experienced in Pytorch for deep learning or C/C++ or Rust for classical algorithms
• Experienced with bioinformatics methods and tools for (a) variant calling, and/or (b) de novo assembly and/or (c) long read sequencing analysis;
• Proficiency in Python, and genomics and machine learning libraries therein.
• Keen interest in programming, algorithm development, mathematics, complexity, and puzzles.

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 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-Assistant-%28Spatial-Computing-Developer%29%2C-Division-of-Industrial-Design/33484-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The research assistant will design and develop software applications and content for the Apple Vision Pro in close collaboration with both the principal investigator along with clinical collaborators for deployment as real-world healthcare applications.

Qualifications

Master’s degree in Design or Computer Science

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-%28National-Centre-for-Engineering-Biology%29/33480-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking one highly motivated and creative postdoctoral researcher to join our dynamic team at the Synthetic Biology for Clinical and Technological Innovation (SynCTI), Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore (NUS) and the National Centre for Engineering Biology (NCEB).  

The selected Research Fellow will work collaboratively with the Principal Investigator (PI) and our research team on projects aimed at advancing sustainable bioproduction. Appointments will be initially made on a 1-year contract, with the possibility of extension. PhD holders with no experience are welcome to apply.

Ideal candidates will possess expertise in metabolic pathway engineering, microbial engineering and the development of cell factories for bioproduction. We particularly encourage applicants with a background in metabolic engineering, genome editing and bioprocess development for biochemical production. The successful candidate will assume a pivotal role in advancing the frontier of synthetic biology to address real-world challenges.

Join us in shaping the future of innovative biotechnology and making significant progress towards sustainability and technological advancement!

Main Responsibilities:
The Research Fellow is expected to: 
1) Develop biological parts, genetic circuits, or tools for engineering microorganisms; 
2) Metabolically engineer microorganisms with high bioproduction capabilities for industrial applications in the production of value-added biochemicals;
3) Write papers together with the PI for publication in high-impact journals;
4) Mentor research assistants, graduate, and undergraduate students; 
5) Assist in any other duties delegated by the Principal Investigator and group leaders. 

Remuneration will be commensurate to the candidate's qualifications and experience. Informal enquiries are welcome and should be made to Ms Suhana Sulaiman, at suhana_s@nus.edu.sg.

Formal application: Please submit your application, indicating job reference number and current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications, oral presentations, and full contacts of 3 referees) to the NUS Career Portal. Only shortlisted candidates will be notified.

Qualifications

Job Requirements:
1) Hold a PhD in Biotechnology, Biological Sciences, Biochemistry, or related disciplines; 
2) Have extensive knowledge and hands-on experience on genetic parts assembly, pathway engineering, microbial strain engineering, fermentation, recovery and analytics of targeted metabolites; 
3) Have the ability to design and perform experiments for microbial strain engineering, gene expression, protein expression, enzymatic assays, microbial fermentation, and product recovery; 
4) Know how to work independently and in a team, have an investigative nature and a strong attention to detail;
5) Possess an established record of international publications

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-%28Chemistry%29/33482-en_GB/?st=8D2D9F15DFBC531D87718EC2F97CDAB3AA51C90A

We regret that only shortlisted candidates will be notified.

Job Description

The successful candidate will work with Prof CHEN Wei on  Interface Engineering for low-dimensional materials based device applications under a project on NRF Investigatorship project:  Interface Engineered Ferroelectric 2D Materials for Artificial Synapses and Neuromorphic Computing”.

The main responsibilities of the position include One postdoc position is available at the Surface and Interface Lab (Prof. CHEN WEI’s group), National University of Singapore. The project focuses on the interface engineering for 2D materials based device and related electrical and optoelectrical characterization for memory and neuromorphic computing application.

The selected candidate will work together with a team comprising experts in MBE growth and STM characterization, device fabrication and related electrical and optoelectrical characterization, and surface reaction mechanism study using home-made interface characterization tools. 

Qualifications

Qualifications / Discipline: PhD in Physics/ Chemistry/ Materials in a research intensive and renowned University or Research Institute. 

Skills: Excellent English writing and communication skill, team management skill, expert in surface and interface science, surface science techniques of low-temperature scanning tunnelling microscopy, q-plus AFM, MBE growth of 2D materials, 2D materials interface engineering, and multi-physics understanding at the integrated device level.

Experience: Extensive research experience and publish at least 3 - 5 first-authored papers on Tier I journals and excellent lab safety management skills and experience.

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-%28Wireless-Optical-Communication-Optical-Memory%29/33481-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Work on hands-on experiments for few of the following tasks:
1. Design, Simulation, and Fabrication of MEMS and Photonics 
2. Design, modelling and testing of Si Photonics
3. Design and set-up testing for high-speed microwave photonics
4. Experience in using the RX6000 and NVidia CUDA toolkit
5.Write 2 or more research papers based on derived data of the above devices in the first year in the top-notch journals
6. Write research grant proposals
7.Supporting and guiding the experiments of MSc students

Qualifications

1. Have learned MEMS, Photonics and high-speed microwave communication system related courses for one semester at post-graduate level and earned score of A- or better.
2. Strong background in hands-on microfabrication techniques at clean room and with journal publications showing such evidences
3. With 1 year and more experience in MEMS design , making and testing MEMS/Photonics
4. Strong knowledge in L-Edit; Lumerical; CST; COMSOL; ANSYS; 
5. Fluent in English speaking and writing
6. Having more than 1 1st-authored international peer-reviewed journal papers, e.g., Nature Communications and Science Advances (for Research Engineer)