2026 Summer/Fall Intern - AI/ML for Systems Biology

2026 Summer/Fall Intern – AI/ML for Systems Biology The AI for Biology & Translation (AIBT) department, housed within the Computational Sciences Center of Excellence, operates at the cutting‑edge intersection of artificial intelligence and translational genomics. Our mission is to accelerate drug discovery and deepen the understanding of complex disease mechanisms by bridging the gap between laboratory insights and clinical applications. Through the development, evaluation, and adaptation of large‑scale, cross‑species foundational AI models such as single‑cell RNA‑seq models, AIBT robustly maps complex cellular states and evolutionarily conserved gene programs between human clinical data and animal disease models. By translating raw biological data into actionable therapeutic targets, the Systems Biology group within AIBT plays a critical role in advancing next‑generation medicine from the bench to the bedside. Responsibilities include: Benchmark and refine large‑scale foundational AI/ML models (e.g., transformer‑based architecture) optimized for cross‑species cell‑type and gene program alignment. Leverage machine learning to identify conserved versus species‑specific cellular responses and map clinical patient phenotypes directly to preclinical mouse phenotypes. Work closely with cross‑functional teams, including AI scientists, computational biologists, and disease‑area experts, to interpret results and develop new lines of research. Document and package clean, reproducible pipelines and code. Summarize findings and present future recommendations in a final oral and poster presentation to the broader AIBT department. Program Highlights Intensive 12‑week, full‑time (40 hours per week) paid internship. Program start dates are in August/September. A stipend, based on location, will be provided to help alleviate costs associated with the internship. Who You Are Required Education Must be pursuing a Master’s Degree (enrolled student) or a PhD (enrolled student). Required Majors – Computational Biology, Bioinformatics, Data Science, Computer Science, Statistics, Bioengineering, Systems Biology, or a related highly quantitative field. Preferred Knowledge, Skills, and Qualifications Strong theoretical and practical foundation in machine learning/deep learning workflows, especially in architectures relevant to high‑dimensional biological data (e.g., Transformers, VAEs, Contrastive Learning). Proficiency in Python and familiarity with machine learning frameworks (PyTorch, TensorFlow) and standard data science toolkits. Prior hands‑on experience handling and analyzing single‑cell genomics data (scRNA‑seq). Excellent communication, collaboration, and interpersonal skills. Relocation benefits are not available for this job posting. The expected salary range for this position based on the primary location of California is $40.00–$50.00 per hour. This position also qualifies for paid holiday time off benefits. Equal Employment Opportunity 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. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing the Accommodations for Applicants form. #J-18808-Ljbffr F. Hoffmann-La Roche AG