Senior Machine Learning Scientist, BRAID (Genomics ML)

A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche.

Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.

The Opportunity

Genentech seeks a highly motivated Senior Machine Learning Scientist to join the Cellular States and their Organization group within the BRAID (Biology Research | AI Development) department in Genentech Research and Early Development (gRED). Our group is committed to designing and implementing transformative Machine Learning capabilities to model and probe the cellular biology of disease, from DNA variation to tissue organization, and how it is manifested in the patient populations we want to impact. These underpin our goal to revolutionize how we discover and characterize novel therapeutic targets and the clinical contexts in which they can be most safe and efficacious. This way, we intend for state (and future)-of-the-art Machine Learning to have material and positive societal impact.

In this position, you will 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. Successful candidates are expected to bring significant experience with image-based biological modalities, demonstrable experience of thoughtfully implementing modern neural network models for biological applications and a deep curiosity for how these will impact therapeutic and target discovery. You will work closely with an existing team of software developers, machine learning experts, computational biologists and wet lab collaborators to develop multimodal tissue Foundation Models. You will immediately impact key ongoing and planned projects in diverse therapeutic areas including Neuroscience, Immunology and Molecular Oncology.

In this role:

• You will lead the application of cutting-edge ML models to address bottlenecks in target discovery and drug development.

• You will collaborate closely with different therapeutic areas and cross-functional teams in gRED to understand needs and concerns.

• You will provide domain specific input to the development of foundation models.

• You will scale ML models to large biological imaging datasets, working at the intersection of deep learning and engineering challenges to support new scientific questions.

• You will regularly publish in top-tier ML, computational biology venues and/or scientific journals, presenting results at internal and external scientific venues, conferences, and workshops.

Who you are

• You have a PhD or equivalent experience in computational biology (e.g. Computer Science, Bioinformatics, Computational Biology, or related technical field).

• You have excellent knowledge of the practice of deep learning and familiarity with modern architectures as demonstrated in past projects and/or publications.

• You have extensive experience with biological imaging modalities and be familiar with the opportunities and limitations of this data modality and its integration with molecular modalities

• You have demonstrated strengths in developing new computational tools and models

• You have a strong publication record at appropriate top-tier venues.

• Advanced skills in Python and Machine Learning libraries such as Pytorch and Pytorch Lightning

• You have strong analytical and written/verbal communication skills.

• 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

Relocation benefits are available for this job posting

The expected salary range for this position, based on the primary location of California, is $167,400 - 310,800. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.

Benefits

#ComputationCoE

#tech4lifeComputationalScience

#tech4lifeAI

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 this form Accommodations for Applicants.