Lecturer/Snr Lecturer (Biomedical Science with Analytics) - Sch of Applied Sc

Public Service Division; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

The Public Service Division is seeking a dedicated educator to shape Pre-Employment Training and Continuing Education & Training, delivering PET/CET curricula and guiding learners through assessments and projects. You will integrate AI and data analytics into teaching, supervise coursework, and build partnerships with industry to enrich real-world learning experiences.

You will mentor students, contribute to curriculum reviews, and use digital tools to enhance engagement, while collaborating

Qualifications

• Minimum 3 years of relevant work experience in a science-related field.
• Experience applying AI, machine learning, predictive analytics or modelling to solve real-world biomedical problems.
• Proficient with analytics tools or programming languages (SAS Viya, Python, SQL, Power BI).
• Strong communication, interpersonal and mentoring skills.
• Candidates will contribute to teaching and curriculum development in predictive analytics and related areas.

Responsibilities

• Develop, deliver and review PET and CET curriculum across face-to-face, online and blended learning.
• Design teaching materials, assessments and authentic projects integrating AI and data analytics.
• Prepare and grade assessments and supervise learners daily.
• Utilise the Learning Management System and digital tools to boost engagement.
• Serve as a Personal Mentor to learners and provide pastoral support.
• Contribute to school initiatives, curriculum reviews and quality assurance.

Skills

Mentoring

Communication

Collaboration

Data analytics tools

Education

Biomedical Science / Life Sciences degree

Tools

SAS Viya

Python

SQL

Power BI

Job description

[What the role is]

You will play an active role in the academic, professional, and personal development of the learners to prepare them for work and life. This includes development of Pre-Employment Training (PET) and Continuing Education & Training (CET) curriculum, programme delivery and working on industry projects.

[What you will be working on]

• Develop, deliver and review PET and CET curriculum, including face-to-face, online and blended learning.
• Design and develop teaching materials, assessments, applied projects and authentic learning activities that include integrating science with AI and data analytics.
• Prepare and grade assessments and supervise learners in their daily course work.
• Use the Learning Management System and interactive digital tools effectively, and harness technology to enhance learner engagement and outcomes.
• Serve as a Personal Mentor to learners, providing pastoral support and assisting with day-to-day academic and administrative matters.
• Contribute to school and diploma-level initiatives, committee work, outreach activities, curriculum reviews and quality assurance processes.
• Build and maintain strong partnerships with industry to lead and develop industry projects, internships and collaborative initiatives.

[What we are looking for]

Highly motivated, resourceful and learner-centric candidates who are nurturing and enjoy interacting with learners with the following:

• Relevant qualifications in Biomedical Science/Life Sciences, with expertise in Clinical Laboratory Sciences and qualifications or experience in Bioinformatics, Data Analytics, Data Science or related disciplines.
• Minimum 3 years of relevant work experience in a science related field.
• Demonstrated experience applying AI, machine learning, predictive analytics or modelling to solve real-world biomedical, healthcare or life sciences problems.
• Proficient in analytics tools or programming languages such as SAS Viya, Python, SQL, Power BI or equivalent.
• Strong communication, interpersonal and mentoring skills, with the ability to collaborate effectively, adapt to changing needs and manage multiple priorities.

Candidates are also expected to contribute to teaching and curriculum development in one or more of the following areas: Predictive Analytics & Forecasting, Predictive Modelling, Database Design & Administration, Data & Statistical methods and Applied Calculus.