Scientist - Research Computational Biology (ARIA)

sights, including characterization of expression biodistribution and isoform complexity.

• Developing advanced capabilities for discovery of novel disease-enriched isoforms using long-read transcriptomics, proteomics, and screening technologies.

• Partnering with our data science and information systems teams to incorporate tools and analyses developed within ARIA Computational Biology into integrated R&D platforms.

Basic Qualifications:

• Ph.D. in computational biology, bioinformatics, data science, or a related discipline OR Master's degree with 3+ years of relevant research experience.

• Strong programming skills (Python, R, Linux/Unix), familiarity with cloud computing environments, HPC, and collaborative coding practices (e.g., Git).

• Track record of designing and executing holistic computational strategies to address challenging research questions.

• Proven expertise in the analysis and interpretation of single cell omics data.

• Excellent presentation and communication skills to convey complex findings to diverse audiences.

• Self-starter with a collaborative mindset and a drive for continuous growth.

Preferred Qualifications:

• Solid immunology background, including application to the interpretation of single-cell oncology and/or inflammatory disease data.

• Strong understanding of RNA and protein isoform complexity, including underlying biology and computational approaches for characterization using long-read transcriptomics.

• Experience leveraging and fine-tuning transcriptional foundation models and biomedical knowledge graphs to further research goals.

• Familiarity with public data resources (e.g. DepMap, Human Cell Atlas, TCGA, GTEx, and Tahoe-100M) frequently used to augment analyses of internally generated data.

• Experience developing and deploying tools and pipelines to endpoints such as interactive portals (e.g. RShiny apps), workflow management systems (e.g Nextflow), and agentic frameworks.

.