Roche and Genentech aim to harness the power of AI, data, and computational sciences to revolutionize drug discovery and development. The goal is to leverage advanced machine learning and biological data integration to discover novel therapeutic targets and improve the safety and efficacy of treatments across various therapeutic areas.
Requirements
- PhD or equivalent experience in computational biology (e.g. Computer Science, Bioinformatics, Computational Biology, or related technical field).
- Excellent knowledge of the practice of deep learning and familiarity with modern architectures as demonstrated in past projects and/or publications.
- Extensive experience with biological imaging modalities and be familiar with the opportunities and limitations of this data modality and its integration with molecular modalities.
- Demonstrated strengths in developing new computational tools and models.
- Strong publication record at appropriate top-tier venues.
- Advanced skills in Python and Machine Learning libraries such as Pytorch and Pytorch Lightning.
Responsibilities
- Lead the application of cutting-edge ML models to address bottlenecks in target discovery and drug development.
- Collaborate closely with different therapeutic areas and cross-functional teams in gRED to understand needs and concerns.
- Provide domain specific input to the development of foundation models.
- Scale ML models to large biological imaging datasets, working at the intersection of deep learning and engineering challenges to support new scientific questions.
- Regularly publish in top-tier ML, computational biology venues and/or scientific journals, presenting results at internal and external scientific venues, conferences, and workshops.
- Lead development and application of next generation ML methods for the representation, analysis and interpretation of image-based data and its integration with molecular data modalities, especially spatial transcriptomics.
- Work closely with an existing team of software developers, machine learning experts, computational biologists and wet lab collaborators to develop multimodal tissue Foundation Models.
Other
- Motivated to learn and apply new Machine Learning techniques working as part of a team with other department members.
- An interest in developing and applying biological foundation models for target discovery and drug development.
- Strong analytical and written/verbal communication skills.
- Relocation benefits are available for this job posting.
