Principal Computational Biologist, Computational Biology

Job Title:

Principal Computational Biologist, Computational Biology

Company: SRT Therapeutics

Reports to: Director of Computational Biology, R&D

Pay Range: $130,000-$215,000

SRT Therapeutics is a San Diego-based biotech company established in 2024 by the founders of Prometheus Biosciences, Steph Targan, MD (Cedars Sinai), Janine Bilsborough, Ph.D. (Cedars Sinai), the scientific team that discovered Tulisokibart (MK7240) and the role of TL1A in IBD as well as Scott Glenn and Lauren Otsuki, the drug development team that took Tulisokibart (MK7240) from academia into the clinic.

Building on the demonstrated success of the precision medicine approach in IBD with Tulisokibart, SRT Therapeutics will expand this approach by targeting key pathways that not only modulate inflammatory pathways, but also promote tissue healing in IBD. This strategy will move SRT Therapeutics beyond the current empirical treatment model to realize the goal of enhancing both outcomes and the quality of care for our patients.

We are seeking a creative and highly motivated Principal Computational Biologist to join our team as the subject matter expert (SME) on machine learning and deep learning (ML/DL). This position will guide SRT’s multimodal data-driven precision medicine strategies in inflammatory diseases by driving our machine learning and deep learning approaches. These approaches will be foundational in identifying, nominating, and validating disease and drug target-associated biomarkers, as well as supporting other research and development initiatives.

The successful candidate will spearhead the application of cutting-edge ML/DL techniques to integrate diverse datasets including public and proprietary bulk/single-cell transcriptomics, genetics, proteomics, histopathology images, and electronic health records (EHR). Working with teams at the intersection of experimental and computational biology, candidate will identify and validate disease biomarkers, drive patient segmentation strategies, and build virtual cell/tissue models for in silico drug screening and drug mechanism of action (MOA) studies.

This work is central to our research, development, and IND-enabling study strategies.

• ML/DL Strategy & Leadership: Serve as the technical lead and SME for machine learning and deep learning initiatives; identify, evaluate, and implement state-of-the-art algorithms (e.g., Transformers, Graph Neural Networks, Multi-instance Learning) for biological problems.
• Multimodal Data Integration: Develop and deploy robust models that fuse heterogeneous data modalities combining high-dimensional omics data (scRNA-seq, spatial transcriptomics) with unstructured data (H&E pathology images, clinical notes/EHR). Proactively identify, evaluate, analyze, and integrate mission-relevant genomic datasets into the company's knowledge base and contribute to evidence generation strategies across clinical trials, precompetitive consortia, and population biobanks.
• Biomarker Discovery & Patient Stratification: Apply predictive modeling to identify novel biomarkers for patient segmentation, pharmacodynamics, and response prediction in inflammatory disease indications; partner with functional biomarker leads across precision medicine and pipeline programs to prioritize target engagement and translational biomarker strategies.
• Virtual Modeling & Simulation: Lead the creation of "virtual cell" and tissue models to perform in silico drug screening and MOA studies to prioritize targets before wet-lab validation.
• Cross-Functional Collaboration: Partner closely with wet-lab biologists to design experiments that generate ML/DL-ready data and translate computational findings into actionable biological hypotheses.
• Pipeline Development: Contribute to scalable, reproducible, and well documented computational pipelines for processing and analyzing large-scale proprietary and public datasets (e.g., genomics assays, multi-omics, imaging, clinical data, UK Biobank, and TCGA), enabling actionable biological insights.
• Mentorship & Communication: Mentor junior computational biologists in ML/DL best practices and…