Research Assistant (Lee Kong Chian Natural History Museum)

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-Assistant-%28Lee-Kong-Chian-Natural-History-Museum%29/33570-en_GB/ We regret that only shortlisted candidates will be notified. Job Description About the Project: The Lee Kong Chian Natural History Museum is developing an AI-assisted biodiversity research platform to support taxonomic research. The project aims to help taxonomists organise, extract, annotate, and connect biodiversity information from taxonomic literature, specimen images, trait data, and other research outputs. Current work involves a range of invertebrate taxa, including flatworms, flies, and sponges. As the project spans different taxonomic groups, the role requires broad biodiversity and taxonomic literacy, rather than specialist expertise in a single group.The project will involve converting taxonomic literature and specimen image data into structured and reusable formats for AI-assisted research workflows. Prior experience with AI, programming, ontologies, or knowledge graphs is not required. Training will be provided. Role Summary: The Research Assistant will support an AI-assisted biodiversity research project through taxonomic literature review, biodiversity data curation, specimen image annotation, project documentation, and coordination of research activities. The role will involve reading and interpreting scientific and taxonomic literature, checking AI-assisted outputs for biological accuracy, organising biodiversity data, annotating specimen images, maintaining clear project records, and assisting with validation by taxonomic experts. The Research Assistant will also help coordinate interns, undergraduate students, student assistants, and collaborators contributing to related project workstreams. This position is suitable for a candidate with a strong biological foundation, good scientific-literature skills, careful data-handling habits, and the ability to work independently in a developing research environment. Prior experience with AI is desirable but not required, as training will be provided on the job. The Research Assistant is not expected to independently develop AI models or software systems, but should be interested in applying biodiversity knowledge to emerging AI-assisted research methods. Key Responsibilities: Biodiversity data curation and literature processing Assist with reviewing taxonomic and biodiversity literature, extracting relevant information, and organising data relating to species, specimens, morphology, traits, images, and source references. Review AI-assisted outputs for accuracy and consistency, and flag uncertain or ambiguous cases for further review. Workflow documentation and quality control Maintain clear records of workflow procedures, curation decisions, expert feedback, data issues, and follow-up actions. Assist in ensuring that project outputs are consistently prepared, traceable to source materials, and suitable for downstream research and AI-assisted workflows. Contribute to refining workflows as project methods develop. Specimen image annotation and data preparation Support the annotation and organisation of museum specimen images and related visual resources. Assist with labelling relevant morphological structures, managing image files and metadata, and preparing structured datasets for project use. Assist with supplementary specimen photography where required, with training and supervision provided. Research, student, and project coordination Liaise with taxonomic experts, project collaborators, interns, undergraduate students, and student assistants to support validation, task coordination, and consolidation of outputs. Assist with project-related meetings, workshops, symposia, and other academic activities, including preparation of materials, logistical coordination, documentation, and follow-up actions where required. Qualifications Bachelor’s Degree in Biology, Life Sciences, Environmental Biology, Ecology, Systematics, Biodiversity Informatics, or a related field. Strong demonstrated ability to read, interpret, and synthesise scientific literature, especially biological or taxonomic literature involving species descriptions, morphological terminology, biological classification, species concepts, diagnostic characters, or trait-based comparisons. Strong organisationa…