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

[What the role is]

[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.

#LI-Hybrid

[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.