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 organisational and project-support skills, including the ability to:

• maintain clear records of project progress, decisions, issues, and follow-up actions;
• follow, document, and adapt structured workflows as project methods evolve; 
• keep track of multiple concurrent tasks and ensure that outputs are completed in a timely and organised manner.

Strong communication, coordination, and self-management skills, including the ability to:

• work independently and take initiative under the supervisor’s direction;
• communicate project updates, issues, and follow-up actions clearly; 
• work constructively in a developing research environment where priorities and workflows may evolve;
• co-ordinate effectively with supervisors, taxonomic experts, students, museum staff, and external collaborators.

Preferred Skills and Experience

Relevant biodiversity, taxonomy, or museum experience, including either or both of the following, preferentially evidenced by published or submitted research output(s):

• Experience or familiarity with taxonomic practice, including how species are described, diagnosed, compared, classified, and named in taxonomic literature.
• Experience or familiarity with biodiversity informatics, including how taxonomic names, species concepts, taxonomic backbones, specimen data, biological collections, and biodiversity databases are organised and used.

Relevant data curation, digital workflow, or AI-related experience, including one or more of the following:

• Experience in data curation, annotation projects, museum informatics, bioinformatics, biological database work, or related research support.
• Prior exposure to AI tools, large language models, image annotation tools, structured data formats, data cleaning, scripting, or reproducible research workflows.
• Interest in AI-assisted taxonomy, biodiversity informatics, digital biodiversity data, and biodiversity research infrastructure.

Relevant imaging and/or annotation experience, including one or more of the following:

• Experience with biological image annotation, specimen photography, microscopy, macrophotography, or preparation of image datasets.
• Familiarity with organising image files, metadata, labels, or visual datasets for research use.

Relevant coordination, communication, or research-support experience, including one or more of the following:

• Experience assisting with student projects, internships, workshops, symposia, academic coordination, or science communication.
• Experience helping to coordinate collaborators, students, volunteers, or project contributors in research, curation, annotation, or documentation tasks.