Postdoctoral Fellow – Regulatory Language Understanding (ReLU) Lab Full-time NEW

Postdoctoral Fellow Position at Genentech

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.

Key research areas include:

• Mechanisms of Common and Rare Genetic Variations: Investigate the molecular mechanisms underlying genetic variations, elucidating how these variants influence gene regulation and contribute to health and disease states
• Design of Non-Coding Genome Edits: Develop innovative machine learning approaches for designing precise non-coding genome edits, focusing on how non-coding alterations influence gene regulation and cellular function
• Disruptions in Post-Transcriptional Regulatory Processes: Analyze how alterations in RNA processing, stability, and translation contribute to cellular dysfunction and disease pathogenesis using mechanistic or quasi-mechanistic models
• Multi-Agent AI Systems for Scientific Discovery: 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.

We seek a highly motivated postdoctoral candidate with expertise in AI, machine learning, and computational biology. The successful applicant will leverage these skills to address complex biological questions. Essential qualifications include a strong publication record, excellent communication abilities, good sense of humor and a collaborative mindset to thrive in our dynamic research environment.

The opportunity includes:

• 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

Who you are:

• 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

Preferred qualifications:

• 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

The expected salary range for this position based on the primary location of South San Francisco California is $110,000 to $120,000. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for the benefits detailed at the link provided below.

Relocation benefits are available for this job posting.

About Genentech's Postdoctoral Program: Elevate your research career to new heights with Genetech's Postdoctoral Program! Join a prestigious community of early career scientists and kick-start your journey toward becoming a scientific leader in biotechnology and bioengineering. With competitive salaries and fully funded research expenses, you can dedicate yourself to groundbreaking research that aligns with Genentech strategic ambitions.

The postdoc program is designed to empower recent Ph.D. graduates to conduct world-class research, publish in top-tier journals, and build a robust scientific network. By joining us, you will receive the mentorship and support necessary to develop into an independent scientist and leader. Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.