Senior Scientist I, Computational Biology (targetID)

HAYA Therapeutics • San Diego, CA

5d

About The Position

At HAYA Therapeutics, we are pioneering a new class of programmable RNA-guided therapeutics that target the regulatory genome to reprogram disease-driving cell states. By decoding the causal biology of pathological cell states and the long-noncoding RNAs (lncRNAs) that regulate them, HAYA translates these insights into tractable therapeutic candidates designed to address disease at its source and restore cellular health. HAYA is advancing a broad pipeline of RNA-guided medicines for chronic, age-related diseases. Recognized globally for our scientific innovation, HAYA has been named a 2025 Technology Pioneer by the World Economic Forum (WEF), selected for BioSpace's NextGen Bio Class of 2026, recognized as a 2026 Disruptive Pioneer by IDEA Pharma, and celebrated as one of the Top Innovative Companies in Switzerland for 2025. As a fast-growing biotech, we offer an entrepreneurial, science-driven environment where you’ll have a direct impact on shaping our pipeline and advancing RNA medicine. The purpose of the role is to execute Target Discovery and Validation activities within the Data Science team to identify and validate cell-state driving disease-modifying lncRNAs and regulatory elements by integrating multi-omics transcriptomics and epigenomics datasets, with main focus on immunology and inflammatory indications.

Requirements

• PhD in Computational Biology, Bioinformatics, Computer Science, Genomics, or a related quantitative or life sciences field with a robust computational focus; or equivalent demonstrated capability and technical depth.
• Proficient programming skills in R or Python, supported by strong data hygiene, and a desire to build shared reproducible toolkits and pipelines.
• Experience on the identification of novel targets, demonstrating a strong drive to design and leverage computational workflows with minimal supervision.
• Deep technical proficiency in preprocessing, integrating, and analyzing multi-omics datasets, specifically bulk and single-cell/single-nuclei RNA-seq, ATAC-seq, PRO-seq, and CUT&RUN, to define cell states and identify biological drivers within the regulatory genome.
• Excellent scientific understanding of gene regulation, transcriptomics, and the non-coding genome (in particular lncRNAs) and gene regulatory networks.
• Proven capability in presenting complex multi-omics statistical analyses, and data science concepts in a clear, narrative-driven manner to both technical, biological, and non-expert stakeholders, serving as a bridge between dry and wet lab activities.

Nice To Haves

• Biological expertise in immunology, inflammatory indications, or immune cell profiling, with the ability to contextualize transcriptomic discoveries in the frame of chronic pathology (highly desired).
• Work within scalable server and cloud automation standards, write reproducible scripting templates, and keeps data science analysis standards that raise the technological bar for the entire Data Science & AI department.
• Demonstrated history of fostering a collaborative scientific culture by providing code reviews, guiding junior analysts on data science best practices, and ensuring strict adherence to reproducible computational biology.

Responsibilities

• Preprocess and analyze raw multi-omics datasets (including bulk/single-cell/single-nuclei RNA-seq, ATAC-seq, PRO-seq, CUT&RUN, 3D genomics) to characterize the regulatory genome driving cell states and extract the features to perform target identification.
• Integrate human genomic, genetic, and epigenetic datasets (including GWAS, eQTLs, and chromatin conformation annotations) with internal transcriptomic pipelines to identify potent cell-state driving lncRNA targets.
• Translate high-dimensional omics analysis and results into clear, biologically grounded scientific presentations and documentation to facilitate strategic alignment, influence multi-disciplinary program stakeholders, and support executive decisions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree