"Research Assistant (Lymphoma Biomarkers, Digital Pathology & Spatial Omics)"

Job Description

The Department of Pathology at the National University of Singapore invites applications for a Research Assistant to join a multidisciplinary team studying haematolymphoid malignancies, with a focus on lymphoma. The lab integrates genomics, digital pathology, and advanced spatial platforms to advance biomarker discovery and pre-clinical testing of novel therapeutic agents. Your contributions will support improvements in diagnosis, prognosis, and therapeutic targeting for patients with lymphoma.

Key Responsibilities

• Tissue-based workflows: Organise pathology slides and tissue blocks; perform tissue sectioning and staining; conduct immunohistochemistry (IHC) and optimise/analyse multiplex immunofluorescence (mIF).
• Tissue microarrays (TMAs): Select cases and coordinate TMA construction.
• Digital pathology: Scan slides using commercial slide scanners and participate in image analysis.
• Spatial omics: Coordinate spatial transcriptomics and proteomics experiments on platforms such as 10x Genomics Visium and NanoString GeoMx/CosMx.
• Data handling and reporting: Maintain accurate laboratory records; analyse and consolidate experimental results; prepare reports, figures, and presentations for internal meetings and collaborators.
• Compliance and operations: Adhere to laboratory SOPs, biosafety, and ethical guidelines; contribute to inventory, equipment maintenance, and general lab operations.

Qualifications

• Bachelor’s degree in life sciences, biomedical sciences, biochemistry, or a closely related field from a well-recognised university.
• Hands-on experience with histology or tissue-based workflows; prior experience with FFPE tissue in a clinical histopathology laboratory or research setting is preferred.
• Strong organisational skills, attention to detail, and excellent written and oral communication.
• Ability to work independently and collaboratively in a diverse, interdisciplinary research environment.

Preferred (advantageous but not required)

• Experience with IHC/mIF optimisation, slide scanning, and digital image analysis (e.g., HALO, QuPath).
• Familiarity with spatial omics platforms (10x Visium, NanoString GeoMx/CosMx).
• Basic data analysis skills (e.g., image quantification pipelines; R/Python exposure).

What We Offer

• Training and mentorship in advanced spatial transcriptomics/proteomics, digital pathology pipelines, and reproducible research practices.
• Collaboration opportunities with pathologists, oncologists, and computational biologists.
• Opportunities for co-authorship on publications and conference presentations, commensurate with contribution.
• A supportive and inclusive lab culture focused on rigorous, patient-impactful science.

Other and Contact

Representative Publications

• PMID: 38459052 (https://pubmed.ncbi.nlm.nih.gov/38459052)
• PMID: 35021606 (https://pubmed.ncbi.nlm.nih.gov/35021606)

Application Procedure:

• Curriculum vitae (including education, relevant experience, and a list of technical skills)
• Cover letter (briefly describe your fit, motivation, and earliest start date)
• Academic transcript(s) (unofficial copies accepted at application stage)
• Contact information for 3 referees

Only shortlisted candidates will be notified. Applications will be reviewed on a rolling basis until the position is filled.

For enquiries, please contact Prof Ng Siok Bian, ng.siok.bian@nus.edu.sg Dr Reagan Entigu, reagan.e@nus.edu.sg.

More Information

Location: Kent Ridge Campus

Organization: Yong Loo Lin School of Medicine

Department: Pathology

Employee Referral Eligible: No

Job requisition ID: 31310