About 2Strands Biosciences
Cancer recurrence remains one of the biggest threats to survivors—yet current monitoring methods are expensive, and often miss the earliest signs. At 2Strands, we're changing that. We're a precision-oncology startup developing an ultrasensitive yet cost-effective blood test for cancer recurrence monitoring. Our proprietary allele-specific enrichment technology selectively enriches tumor DNA fragments from blood, enabling earlier and more accurate detection of residual disease at a fraction of the sequencing burden.
We're looking for a Bioinformatics Scientist (or Computational Biologist) with strong NGS expertise to design and implement the analysis pipeline that will bring this vision to life. The scientist will also adapt and optimize an existing probe-design workflow and develop an automated panel-selection algorithm from matched tumour-normal WES data. This is a unique opportunity to own the computational backbone of a transformative diagnostic platform—and see your work directly impact patient lives.
What you'll do
- Adapt, validate and further develop cutting-edge UMI-based error-correction algorithms to collapse PCR replicates and reveal ultra-low-frequency variants.
- Create rare-variant calling models optimized for enriched ctDNA fragments, distinguishing true signal from sequencing noise with confidence.
- Partner closely with wet-lab scientists to validate performance on reference and clinical datasets.
- Deliver modular, automation-ready pipelines (Nextflow/Snakemake + containers) designed for clinical scaling. Work closely with experts to translate research-grade algorithms into robust, production-ready workflows suitable for regulated clinical environments.
- Work closely with expert consultants to produce SOPs and documentation that meet regulatory standards and enable clinical validation.
- Adapt, validate, and further optimize an existing probe design workflow for integration into the 2Strands assay development platform
- Develop panel selection algorithms that interrogate matched tumour-normal WES data
Who you are
- PhD ( or equivalent experience) in Bioinformatics, Computational Biology, Genomics, or related field with a strong track record in NGS data analysis.
- Proven experience with UMI processing, variant calling, and statistical modelling of rare mutation events will be highly valued.
- Proficiency in Python, R, and workflow languages (Nextflow, Snakemake).
- Familiarity with ctDNA/MRD assays is a major plus.
- Collaborative, hands-on, and excited to work at the intersection of computational and experimental science.
- Experience in somatic variant calling from tumour-normal WES data using GATK Mutect2, Strelka2, or VarScan2, with experience in tumour purity/ploidy correction (PURPLE, FACETS, or TITAN), copy number analysis (CNVkit, GATK CNV), VCF annotation and filtering (VEP, ANNOVAR, gnomAD/dbSNP germline exclusion), clonality scoring, and VAF-based variant prioritisation for personalised panel selection is preferred.
- Experience with tumour heterogeneity/clonal evolution modelling (PyClone, ABSOLUTE, or equivalent) to inform variant selection strategies that maximise tracking sensitivity across tumour subclones is preferred.
- Candidates from academia with demonstrated expertise in cancer genomics and NGS pipeline development are encouraged to apply
Why join us
- Impact: Your algorithms will directly shape a product that could change how cancer recurrence is detected worldwide.
- Ownership: As an early hire, you'll set the foundation of our computational strategy and influence company growth.
- Momentum: Backed by VC and Enterprise Singapore
- Mission: Join a passionate team determined to make life-saving technology accessible to patients everywhere.
