Senior Machine Learning Scientist
5 days ago
The Position
A healthier future is what drives us to innovate at Genentech. We are committed to advancing science and ensuring everyone has access to the healthcare they need today and for generations to come.
We are seeking a highly skilled and motivated Senior Machine Learning Scientist to join the Perturbation Biology group within the BRAID (Biology Research | AI Development) department in Genentech Research and Early Development (gRED).
Our dynamic and creative team is dedicated to developing the next generation of Machine Learning models to derive actionable insights from large-scale high-content perturbation experiments and to predict the outcome of unseen perturbations to drive experimental design.
We are committed to fostering innovation through cutting-edge ML methods with real-world impact in target and drug discovery.
The Opportunity
We are looking for exceptional researchers with a demonstrated research background in Machine Learning, a passion for interdisciplinary research and technical problem-solving, and a proven ability to develop and implement research ideas.
The candidate is expected to routinely publish work in top-tier Machine Learning and scientific venues.
Responsibilities
- Design and apply Machine Learning algorithms to guide and improve the experimental design of high-content perturbation screens for drug and target identification, employing model classes such as multimodal representation learning and geometric deep learning.
- Work on and integrate a variety of different data modalities such as molecular structures, omics data, images, and text.
- Collaborate with interdisciplinary and cross-functional teams including biologists, chemists, data scientists, and other stakeholders.
- Build and scale Machine Learning techniques to massive datasets and aid in the deployment of novel Machine Learning algorithms.
- Publish in top-tier ML venues and/or scientific journals, present results at internal and external scientific venues, conferences, and workshops.
Requirements
- PhD degree in quantitative field (e.g., Computer Science, Statistics, Mathematics) or in the physical or life sciences (e.g., Chemistry, Biology) with a strong quantitative focus.
- Proven track record of developing and applying advanced ML models in a research or industry setting.
- Demonstrated interest in problems across biology and chemistry as applied to the discovery and development of treatments for disease.
- Proficiency in scientific programming in Python.
- Extensive experience with Machine Learning frameworks and libraries (e.g., PyTorch, JAX, Tensorflow).
- Strong background in statistics, probabilistic modeling and data analysis.
- Excellent communication, collaboration, and problem-solving skills.
- Strong publication record and experience contributing to research communities, including conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, etc.
Preferred
- Practical experience in one or more of the following areas:
- Predictive modeling of perturbation datasets with high-content readout (e.g., transcriptomics or image data)
- Modeling perturbation effects on heterogeneous cell states in transcriptomics data
- Predictive modeling and/or generative modeling on molecules and other chemistry applications
- Multimodal data integration, in particular between multiple measurement modalities and/or clinical patient data
Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.
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