Postdoctoral Fellow - Regulatory Language Understanding (ReLU) Lab

Roche • South San Francisco, CA

125d • $110,000 - $120,000

About The Position

A postdoctoral fellow position is available in the ReLU lab, led by Gokcen Eraslan within the Biology Research AI Development (BRAID) department of Genentech's Computational Sciences Center of Excellence (CS-CoE) organization. This role offers a unique opportunity to contribute to cutting-edge research at the intersection of artificial intelligence and regulatory genomics, developing and applying state-of-the-art computational methods to critical scientific challenges. The primary focus of this postdoctoral role will be developing and applying advanced AI models and sophisticated multi-agent systems to address pressing challenges in regulatory genomics.

Requirements

• Ph.D. in Computational Biology, Bioinformatics, Computer Science, Machine Learning, or related field with focus on genomics or regulatory biology.
• Demonstrated proficiency in Python and machine learning frameworks (e.g. PyTorch, Jax, scikit-learn) applied to genomic datasets.
• Experience with various sequence modeling architectures and interpretable AI methods (attribution methods including SHAP, Integrated Gradients, etc.).
• Proven ability to communicate complex bioinformatics concepts to both technical and non-technical audiences, evidenced by first-author publications in peer-reviewed journals.
• Independent, highly motivated, and collaborative researcher able to work effectively with multidisciplinary teams of computational and experimental biologists.

Nice To Haves

• Experience with genomic foundation models (e.g., Decima, Enformer, Evo2).
• Experience with RNA sequence models (e.g. Saluki, Orthrus, RiboNN).
• Background in bulk and/or single-cell omics data analysis (genomics, transcriptomics, scRNA-seq, Perturb-seq) with deep understanding of gene regulation.
• Familiarity with agentic frameworks (LangChain, LangGraph, AutoGen, Google ADK) and their applications in biological contexts.
• Experience applying computational linguistics, NLP, and NLU practices to regulatory genomic language, including sequence grammar analysis, motif semantics, and regulatory syntax modeling.
• Passion for translational research in genomics, drug discovery, and therapeutic development.
• Strong ideation skills with ability to rapidly prototype and evaluate new concepts.
• Intellectual curiosity and courage to boldly pursue innovative research directions.
• Ability to excel in a fast-paced, evolving research environment.

Responsibilities

• Investigate the molecular mechanisms underlying genetic variations, elucidating how these variants influence gene regulation and contribute to health and disease states.
• Develop innovative machine learning approaches for designing precise non-coding genome edits, focusing on how non-coding alterations influence gene regulation and cellular function.
• Analyze how alterations in RNA processing, stability, and translation contribute to cellular dysfunction and disease pathogenesis using mechanistic or quasi-mechanistic models.
• Pioneer the development of multi-agent computational systems where specialized AI agents collaborate to solve complex genomic challenges, including data analysis, hypothesis generation, and experimental design optimization.
• Work closely with experimental colleagues to build, train, and evaluate cutting-edge AI models and multi-agent systems for regulatory genomics.
• Leverage multimodal high-dimensional data to investigate relationships between genetic variations and gene regulation in disease contexts.
• Conduct exploratory research in a fast-paced environment with potential for significant impact on understanding and treating diseases related to gene dysregulation.
• Receive technical and scientific mentorship from computational and experimental colleagues while developing and testing biological hypotheses.
• Present at international scientific conferences and publish models and insights in high-impact journals.

Benefits

• Relocation benefits are available for this job posting.
• Competitive salaries and fully funded research expenses.
• Access to world-class seminars, professional development workshops, and networking opportunities.

What This Job Offers

• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees