Scientist, Translational Genomics - San Diego, CA

Mirador Therapeutics, Inc.•San Diego, CA

4h•$120,000 - $175,000•Hybrid

About The Position

Mirador Therapeutics, Inc. is a clinical-stage precision medicine company focused on developing first-and/or best-in-class next-generation therapeutics for immunology and inflammation. The company’s Mirador360™ precision development engine leverages the latest advances in human genetics and data science to rapidly deliver new precision medicines for patients living with immune-mediated inflammatory and fibrotic diseases. Mirador has raised over $650 million from leading life sciences investors and is based in San Diego, CA. Mirador was named Best Places to Work by Biospace and is a Great Place to Work-Certified™ Company. Summary We are seeking a talented translational genomics scientist to integrate and analyze multi-omics data, including genetics, transcriptomics, single-cell, medical imaging, and electronic health records—to accelerate drug development in immunology and inflammation. The successful candidate will design and execute genomics studies to identify and prioritize novel drug targets, optimize combination or multi-specific antibody regimens, and develop predictive models for treatment outcomes and patient stratification. The primary focus of this role will be the analysis of multi-omics and biomarker data to support clinical trials. This position is based in San Diego, CA; may consider exceptional remote candidates.

Requirements

Ph.D. in Computational Biology, Bioinformatics, Computer Science, Engineering, Statistics, or related discipline is required.
3 or more years of post-graduation or biotech and/or pharmaceutical industry experience is required.
2 or more years of relevant biotech and/or pharmaceutical industry experience in a related field.
Proficiency in at least one high-level programming language (e.g., R, Python, or C/C++) with demonstrated experience in complex data analysis and reproducible research practices.
Expertise in multi-omics data integration, including genetics, bulk RNA-seq, and single-cell RNA-seq, to identify genomic signatures underlying disease mechanisms and therapeutic responses.
Recognized as a subject matter expert (SME) in statistical genetics, GWAS/QTL integration, causal inference/discovery, or polygenic risk modeling, with a solid understanding of machine learning and systems biology.
Proven track record of contributing to and advancing cross-functional, multi-disciplinary research projects.
Excellent interpersonal and communication skills, with the ability to distill complex scientific data into clear, actionable insights that support strategic decision-making.
Strong work ethic and proactive problem-solving mindset, fostering effective scientific collaboration and driving projects toward successful outcomes.
Thrives in dynamic, fast-paced, and collaborative environments, working effectively with diverse teams across disciplines.

Nice To Haves

Background in inflammatory or autoimmune diseases, and experience in translational research, including biomarker data analysis for clinical trials, are highly desirable.

Responsibilities

Design and execute genomic studies to uncover causal mechanisms underlying immune-mediated and inflammatory diseases by integrating multi-omics data from both public and proprietary sources.
Collaborate with the Immunology team and the broader R&D organization to provide data-driven guidance on study design, drug target validation, combination target nomination, and indication expansion for clinical assets.
Utilize genomic markers to predict treatment responses and stratify patient subpopulations through network and pathway analyses integrating multi-omics datasets and preclinical or clinical efficacy data.
Partner with internal teams (Immunology, AI) and external collaborators (academic and industry) to collect functional data and develop systems biology and machine learning approaches that accelerate drug discovery and development.
Contribute to and oversee translational study plans, author scientific reports, and present methods, findings, and conclusions to a publication-ready standard.
Communicate analysis strategies and scientific insights to members of cross-functional teams—including biologists, clinicians, and leadership—to inform research and development decisions.