Senior Scientist, Target Discovery for Nucleic Acid Drugs

Planet Pharma; Singapore; On-site; SGD 150,000 - 210,000; Full time

Job summary

Planet Pharma in Singapore partners with a major biomedical organisation building a translational drug discovery platform focused on nucleic acid medicines. The successful candidate will join as Scientist or Senior Scientist in Computational Biology and Target Discovery to identify, prioritise and validate novel therapeutic targets for cardiometabolic diseases.

This role integrates human genetics, multi-omics and disease biology to determine targets for siRNA, ASO and related RNA modalities,

Qualifications

• A PhD in Biology, Genetics, Genomics, Bioinformatics, Pharmacology, Computational Biology or a related discipline.
• Approximately 5+ years’ relevant experience for Scientist level and 10+ years for Senior Scientist level, ideally within pharmaceutical or biotechnology drug discovery.
• Strong experience in therapeutic target discovery, human genetics and/or translational disease biology.
• Deep understanding of metabolic disease biology, ideally including MASH, obesity or related cardiometabolic disorders.
• Proven experience integrating and interpreting large-scale human genetics and multi-omics datasets.
• Strong understanding of the difference between correlative biological signals and evidence supporting causal disease relationships.
• Experience identifying, prioritising and progressing novel targets through early drug discovery.
• Proficiency in Python and/or R for analysis, visualisation and development of computational frameworks.
• Ability to work effectively with specialist bioinformatics teams while maintaining ownership of the biological and drug discovery question.
• Familiarity with siRNA, ASO or other nucleic acid therapeutics and an understanding of how target biology, tissue expression and delivery influence therapeutic feasibility.
• Strong scientific communication skills and the ability to turn complex data into clear decisions for multidisciplinary drug discovery teams.

Responsibilities

• Identify and prioritise novel therapeutic targets across MASH, obesity and broader metabolic disease.
• Integrate human genetics, real-world evidence and multi-omics data to build compelling target hypotheses.
• Apply evidence from GWAS, rare variant analysis, transcriptomics, proteomics, metabolomics and lipidomics to target discovery.
• Translate complex computational findings into clear biological hypotheses and actionable drug discovery decisions.
• Investigate disease-relevant pathways across liver, adipose tissue and muscle biology, identifying opportunities for therapeutic intervention.
• Develop structured approaches for evaluating target confidence, biological rationale, clinical relevance and druggability.
• Assess whether targets are suitable for intervention using siRNA, ASO or related RNA-based modalities, including consideration of tissue accessibility and delivery.
• Work closely with computational scientists, biologists and pharmacologists to build fit-for-purpose target validation strategies.
• Connect target biology with relevant translational biomarkers and clinical endpoints.
• Drive clear go / no-go recommendations for individual targets and help build a continually evolving pipeline of opportunities.
• Provide scientific leadership across cross-functional target discovery activities and communicate complex computational evidence to both computational and non-computational colleagues.

Skills

Python

R

Multi-omics integration

Target discovery

Data interpretation

Education

PhD in Biology/Genetics/Genomics/Bioinformatics/Pharmacology/Computational Biology or related

Tools

GWAS analysis

Multi-omics platforms

Job description

Planet Pharma in Singapore partners with a major biomedical organisation building a translational drug discovery platform focused on nucleic acid medicines. The successful candidate will join as Scientist or Senior Scientist in Computational Biology and Target Discovery to identify, prioritise and validate novel therapeutic targets for cardiometabolic diseases.

This role integrates human genetics, multi-omics and disease biology to determine targets for siRNA, ASO and related RNA modalities,