Scientist/Senior Scientist, Computational Oligonucleotide Design

We are seeking a Computational Scientist to develop predictive models and computational pipelines for the design and optimization of RNA therapeutics, including ASOs, siRNAs, and mRNAs. The successful candidate will leverage bioinformatics, AI/ML, and RNA biology to accelerate candidate discovery, support translational research, and contribute to NATi’s platform innovation and intellectual property portfolio.

Key Responsibilities

• Develop and scale computational pipelines for RNA therapeutic design and optimization.
• Build automated data processing and visualization workflows to evaluate target specificity, pharmacological properties, and cross-species applicability.
• Apply AI/ML approaches to predict oligonucleotide efficacy, toxicity, and other drug properties.
• Analyze large-scale biological datasets, including transcriptomics, structural, and sequence data, to guide candidate design.
• Develop predictive models integrating RNA sequence, structure, and chemistry to support target engagement and candidate selection.
• Collaborate with chemists, biologists, and pharmacologists to translate computational insights into experimentally validated candidates.
• Stay current with emerging computational tools and advances in RNA therapeutics.
• Contribute to intellectual property generation, technical reports, and stakeholder presentations.

Qualifications & Experience

• PhD in Computational Chemistry, Biophysics, Bioinformatics, Biomedical Engineering, or a related field.
• Minimum 4 years (Scientist) or 8 years (Senior Scientist) of industry experience in computational oligonucleotide design or RNA therapeutics.
• Strong programming and data analysis skills in Python and/or R, with experience applying AI/ML methods to biological or chemical datasets.
• Proficiency in RNA structure prediction and interaction modeling tools such as ViennaRNA, RNAstructure, IntaRNA, or RNAhybrid.
• Experience with RNA-seq analysis, sequence analysis tools, and oligonucleotide design platforms.
• Strong understanding of RNA biology, including splicing, RNA editing, polyadenylation, and RNA-binding proteins.
• Knowledge of nucleotide modification strategies and their application to RNA therapeutic design.
• Experience combining physics-based and AI/ML approaches for predicting oligonucleotide properties is advantageous.
• Proven ability to work effectively in multidisciplinary teams and communicate computational insights to experimental scientists.
• Strong problem-solving skills and ability to thrive in a fast-paced research environment.
• This position is based in Singapore. Successful candidates must be willing to relocate to Singapore.