Senior Scientist, Translational Omics & Bioinformatics

About Oxia

Oxia Therapeutics is pioneering a new class of medicine that reawakens the body's innate repair systems to restore health at the cellular level. We are a team of scientists and innovators dedicated to translating bold science into commercial products with significant beneficial societal impact. Our CEO is an experienced former Pfizer executive who built the business unit he was responsible for into a $2.5B portfolio. Our CFO has 40 years of experience in the life sciences industry.Tips: Provide a summary of the role, what success in the position looks like, and how this role fits into the organization overall.

About the role

Oxia is hiring a Senior Scientist in Translational Biology to lead hands-on experimental work in our cellular repair platform and to provide first-pass analysis of the data we generate. This is a hybrid bench-and-computational role designed for a scientist who can run their own experiments, analyze their own data, and engage iteratively with a part-time bioinformatics consultant for deeper analytical work.

This is the right role for Oxia's current stage. We are building toward an internal bioinformatics function but are not yet at the data volume that justifies a dedicated full-time computational hire. The Senior Scientist, Translational Biology will be primarily a bench scientist whose computational fluency lets us move quickly from data generation to biological interpretation without waiting on outsourced analyses for routine work.

This is a hands-on, high-impact role for someone excited to operate in a small-company environment where scientific judgment, execution speed, and cross-functional communication matter.

Key responsibilities:

Hands-on experimental work — primary responsibility

•     Design, execute, and interpret in-vitro and in-vivo experiments to advance Oxia's mechanism-of-action, translational, and biomarker programs.

•     Lead omics study design and execution — sample planning, study logistics, partnering with CROs and academic collaborators on data generation.

•     Run hands-on cell-based and molecular biology assays including mammalian cell culture, RNA-seq sample preparation, qPCR validation, Western blotting, and ELISA-based biomarker assays.

•     Generate publication-quality data with rigorous experimental design, appropriate controls, and reproducible methods.

•     Author SOPs and methods for experimental protocols you develop or validate.

First-pass data analysis and interpretation

•     Perform first-pass analysis of omics datasets from your own experiments and Oxia's broader program — including RNA-seq QC, differential expression, and pathway analysis.

•     Use Python or R workflows for routine analyses. Maintain reproducible analytical practices (version control, environment management, documented workflows).

•     Engage with the bioinformatics consultant on deeper analytical questions — multi-omic integration, custom integrative analyses, mechanistic modeling.

•     Translate analysis output into biological interpretation, experimental hypotheses, and program decisions.

•     Maintain a clean, organized analytical environment that a future full-time bioinformatician can extend without rebuilding.

Translational and biomarker strategy

•     Partner with scientific leadership to develop pharmacodynamic and disease biomarkers connected to drug target engagement, tissue repair, and downstream phenotypes.

•     Generate experimental and analytical recommendations that link mechanism studies to indication selection and clinical biomarker hypotheses.

•     Contribute to manuscript writing, scientific presentations, and regulatory-supporting scientific narratives.

Cross-functional partnership

•     Work closely with internal scientists, CRO partners, and external academic collaborators to oversee study design, data generation, quality review, and interpretation.

•     Serve as the scientific point of contact for the bioinformatics consultant relationship — translating program needs into analytical scopes of work.

•     Contribute scientific judgment to program decisions on lead nomination, indication focus, and IND-supporting study planning.

Required qualifications

•     Education. PhD in molecular biology, cellular biology, biochemistry, pharmacology, translational research, or a closely related life-science discipline.

•     Industry biotech experience. Years of post-PhD experience in biotech, pharma, or a strongly translational academic setting. Candidates with only academic experience should have publication track records and translational orientation evident from their research.

•     Hands-on bench expertise. Demonstrated experience designing and executing experiments in cell-based and molecular biology systems. Specifically: mammalian cell culture under sterile conditions, RNA/DNA extraction, qRT-PCR, Western blotting, and ELISA.

•     RNA-seq and ATAC-seq experience — both ends. Has personally led RNA-seq experiments from sample preparation through downstream analysis. Can design an RNA-seq study (powering, batch design, controls), prepare quality libraries, and analyze the resulting data.

•     Intermediate-to-strong computational fluency. Comfortable with Python or R for biological data analysis. Specifically: can perform differential expression analysis (DESeq2, edgeR, or limma), pathway analysis (GSEA, MSigDB, or similar), basic data visualization (ggplot2, matplotlib, seaborn), and routine QC of sequencing data. Familiarity with version control (git/GitHub) and reproducibility practices is expected for a senior hire.

•     Translational orientation. Can connect mechanism studies, omics data, and biology to therapeutic hypotheses and program decisions. Has experience with biomarker development, indication selection logic, or translational study design.

•     Communication. Strong written and verbal communication, including the ability to distill complex experimental and analytical work into clear slides, memos, and publication-quality narratives.

Preferred qualifications

•     Prior experience in tissue repair, stress response biology, ischemia-reperfusion injury, or cardiac/neuronal repair.

•     Experience with multi-omic data types (ATAC-seq, proteomics, single-cell RNA-seq) beyond bulk RNA-seq.

•     Experience with pharmacodynamic biomarker development for small-molecule drug programs.

•     Prior experience working with bioinformatics consultants or contractors and managing the relationship for sustained analytical productivity.

•     Publications in tissue repair, transcription biology, or translational pharmacology.

•     Experience contributing to IND-supporting scientific packages.

Additional skills considered a plus

•     Experience in one or more of the following: virtual screening, structure-based and ligand-based approaches for small-molecule design, physicochemical property and ADMET optimization using ML models.

•     Knowledge of the drug-discovery process and screening data analysis.

•     Experience using AI/ML methods for protein structure prediction and design.

•     Strong knowledge of chemical and protein structure.