Job Description

Professor Lee Soo Chin's laboratory at Cancer Science Institute of Singapore is seeking a highly motivated Research Assistant to join Professor Lee Soo Chin’s laboratory, which focuses on developing novel therapeutics and predictive biomarkers in breast cancer. The successful candidate will support ongoing research projects related to breast cancer treatment strategies, pharmacogenetics, and inter-ethnic differences in therapeutic response.

Key Responsibilities:

• Conduct laboratory experiments involving cell culture, molecular biology, and biochemical techniques (e.g., PCR, Western blotting, ELISA, qPCR, flow cytometry).
• Assist in preclinical studies, including drug treatment experiments and analysis of tumor models.
• Perform genomic and transcriptomic analyses of breast cancer samples, including cell-free DNA detection and biomarker validation.
• Support clinical research by processing patient-derived samples and analyzing pharmacokinetics and pharmacodynamics data.
• Maintain accurate records of experimental procedures, results, and protocols.
• Assist in data analysis and interpretation, contributing to the preparation of research papers, reports, and presentations.
• Collaborate with other researchers, clinicians, and industry partners on translational research projects.
• Ensure compliance with laboratory safety and ethical guidelines.

Requirements:

• Bachelor's or Master’s degree in Life Sciences, Biomedical Science, Molecular Biology, Pharmacology, or a related field.
• Hands-on experience in laboratory research, preferably in cancer biology, pharmacogenetics, or molecular oncology.
• Proficiency in cell culture techniques, molecular biology methods, and bioinformatics tools is advantageous.
• Strong analytical and problem-solving skills with attention to detail.
• Ability to work independently as well as in a team environment.
• Excellent written and verbal communication skills.
• Prior experience with clinical research, biomarker discovery, or pharmacokinetics studies is a plus.

Preferred Qualifications:

• Experience with next-generation sequencing (NGS) and liquid biopsy techniques.
• Knowledge of statistical analysis and computational biology tools for genetic and pharmacokinetics data.