About NATiThe Nucleic Acid Therapeutics Initiative (NATi), hosted by A.STAR, is Singapore's national platform dedicated to advancing RNA-based medicines and revolutionising drug and vaccine development. NATi's mission is to establish Singapore as a globally recognised hub of excellence in nucleic acid therapeutics research, clinical translation, and commercialisation.
NATi focuses on key RNA modalities such as antisense oligonucleotides (ASOs), small interfering RNA (siRNA), and messenger RNA (mRNA). To drive this vision, NATi is building a biotech-like translational engine focused on asset and technology development spanning discovery to clinical development.
We are actively seeking passionate and committed individuals with deep translational expertise to join us in advancing the next generation of RNA-based therapeutics.
Position OverviewWe are seeking an experienced Senior Scientist (Target Discovery & Validation), Cardiovascular & Metabolic Diseases with deep expertise in human disease biology and target discovery to lead the identification and validation of novel targets druggable with RNA modalities for MASH, obesity, and skeletal muscle-related metabolic disorders. This role provides scientific leadership for early-stage target identification and validation using human genetics, multi-omics, and disease biology-driven approaches. The successful candidate will translate complex human datasets into actionable, prioritised targets suitable for siRNA/ASO development.
The successful candidate will bring his/her mechanistic understanding of liver, adipose, and skeletal muscle biology and the ability to interrogate and integrate large-scale human cohort data while working closely with bioinformaticians and computational biologists to deliver a high-quality, strategically aligned portfolio of novel targets.
Key Responsibilities
Lead Target Discovery: Own and advance a rolling portfolio of genetically and mechanistically supported targets for RNA therapeutics in MASH, obesity, and skeletal muscle related metabolic disorders, ensuring alignment with strategic and translational goals
Translate Human Data into Actionable Biology: Integrate human genetics and multi omics datasets to generate clear, testable hypotheses, mechanistic rationales, and strategies that link target modulation to clinically meaningful outcomes
Decision-Grade Target Selection: Establish and apply a standardised target ranking framework that supports transparent go / no-go decisions and reduces downstream attrition
Cross-Functional Leadership: Serve as the scientific decision owner for target discovery, aligning bioinformatics, biology, and pharmacology teams around shared milestones and success criteria
Define and Execute Target Enablement & Validation Strategies: Design and oversee fit for purpose validation plans using human relevant models and RNA compatible approaches to generate decision enabling data for advancement or deprioritisation
Human Disease Biology & Target Discovery
Define disease-relevant biological questions in MASH, obesity, and/or muscloskeletal disorders that guide data interrogation and hypothesis generation
Identify causal or disease-modifying pathways across liver-adipose-muscle crosstalk and nominate intervention points amenable to modulation by RNA modalities
Articulate mechanistic rationales linking target perturbation to clinically meaningful outcomes (e.g., fibrosis regression, insulin sensitivity, muscle function)
Target Output: Mechanism-of-action models disease pathway maps target biology briefs supporting investment decisions.
Multi-Omics & Human Genetics Integration
Lead discovery efforts using GWAS, rare variant analyses, transcriptomics (bulk, single-cell, spatial), proteomics, metabolomics, and lipidomics
Partner with bioinformaticians to design analysis plans, define statistical thresholds, and assess causality vs correlation
Triangulate evidence across multiple human datasets to quantify confidence in target-disease relationships
Target Output: Genetically anchored target dossiers reproducible analysis summaries evidence-weighted confidence scores per target.
Target Prioritisation & Clinical Relevance
Apply a quantitative target ranking framework incorporating:
Strength and consistency of human genetic evidence
Disease specificity and biological plausibility
Tissue and cell-type expression
Availability of translational biomarkers and clinical endpoints
Technical feasibility for siRNA / ASO delivery (liver, adipose, muscle)
Explicitly link each prioritised target to clinical endpoints:
MASH: histology, non-invasive fibrosis and inflammation biomarkers
Obesity: metabolic, cardiometabolic, and weight-related outcomes
Skeletal muscle: functional, metabolic, and mitochondrial readouts
Target Output: Ranked target lists with decision rationales documented go/no-go recommendations.
Target Enablement & Validation Strategy
Define fit-for-purpose enablement and validation plans for each advanced target, explicitly designed to demonstrate causal disease relevance and RNA-mediated druggability, specifying:
Human tissue and cell-based validation strategies to confirm target expression, regulation, and disease-associated activity in relevant liver, adipose, and skeletal muscle contexts
Genetic and molecular perturbation approaches (e.g. loss-/gain-of-function, pathway modulation) to establish directionality, mechanism, and downstream biological impact
Disease-relevant in vitro and in vivo models selected to test target engagement, pathway modulation, and phenotypic rescue
Ensure each prioritised target has clear predefined validation objectives, including clear mechanistic hypotheses, quantitative success criteria, and translational biomarkers that enable objective assessment of target validity and risk
Drive generation of decision-enabling validation data sufficient to support advancement into asset generation pipeline or formal deprioritisation
Target Output: Integrated target enablement and validation plans stage-gated validation roadmaps quantitative biomarker and readout strategies aligned to development and decision milestones.
Measures of Success
Percentage of nominated targets progressing into Asset Generation Pipeline
Strength and reproducibility of human evidence supporting advanced targets
Reduction in downstream attrition due to weak biology or poor translatability
Clarity and speed of target-related go / no-go decisions
Quality of cross-functional alignment and scientific decision-making
Qualifications & Professional Attributes
PhD in Biology, Genetics, Genomics, Bioinformatics, Pharmacology, or related discipline
A minimum of 5+ (Scientist), 10+ (Senior Scientist) years of relevant experience in target discovery, human genetics, or translational disease biology in pharmaceutical and/or biotech organisations
Proven expertise in multi-omic data interpretation and integration for complex human diseases
Strong background in metabolic disease biology, particularly MASH, obesity, and/or skeletal muscle disorders
Demonstrated experience working with bioinformaticians and computational biologists on large datasets
Track record of identifying, prioritising, and enabling novel therapeutic targets
Strategic, hypothesis-driven thinker with excellent scientific communication skills
Collaborative leader capable of influencing cross-functional teams under matrix management
Global Recruitment & Competitive CompensationNATi is conducting a global search for top-tier talent in RNA therapeutics. We welcome applications from leading pharmaceuticals scientists and biotech innovators worldwide.
This role provides a highly competitive compensation package aligned with global industry standards, including attractive benefits and long-term career growth opportunities within Singapore's thriving biomedical innovation ecosystem. Join us in shaping the future of RNA-based medicines and establishing Singapore as a world-class hub for nucleic acid therapeutics.
