-
of Dr. Jennie Lill within Genentech’s world-class Department of Proteomic and Genomic Technologies. This position will have a joint appointment with Dr. Anwesha Dey (Molecular Oncology). Our department is
-
Demonstrated proficiency with Python, and machine learning libraries; pytorch, sklearn Experience with transformer architectures, and interpretable AI methods and libraries, concept-bottleneck architectures
-
. 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
-
leveraging collaborations within the group and across Research & Development. Who You Are: PhD in Computational Biology, Computer Science, Applied Mathematics, or similar field Demonstrated record
-
hypotheses. This is a fantastic opportunity to contribute to world-class science in a leading biotechnology company. Who you are: Candidates must have a PhD in Computational Biology or Computational Science
-
vulnerabilities. The Genentech scientific community provides access to generous state-of-the-art resources, cutting-edge technologies, and a collaborative network of leading cancer biologists, immunologists, and
-
The Position We advance science so that we all have more time with the people we love. The Proteomics and Genomics Technologies department develops and employs innovative proteomic and genomic
-
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
-
: Ph.D. in physics, applied mathematics, statistics, computer or computational sciences, or in an engineering field such as biomedical informatics, or a related discipline. Required experience in
-
that combine the engineering and analytical principles of multiple scientific disciplines. We are seeking a talented postdoctoral fellow to join our team and advance our mission by contributing to the discovery