The Position 2024 Summer Intern – Biochemical and Cellular Pharmacology AI This internship position is located in South San Francisco, on-site. Department Summary The mission of the Biochemical and Cellular Pharmacology (BCP) department is to develop relevant quantitative biochemical and cellular assays, including unbiased phenotypic screening, to support both biological and small molecule drug discovery efforts at Genentech. Phenotypic screening in BCP has historically focused on high-content imaging of cellular morphology before and after compound-induced perturbation. Morphological similarity to annotated perturbations can help to elucidate MoA and guide hit expansion. Complimentary profiling modalities, including transcriptomics, are now commonly performed alongside imaging. However, machine learning approaches for learning on these multi-modal data are still in their infancy. We are seeking to develop and apply cutting-edge methods to analyze multimodal data, with a particular focus on applying deep learning models to imaging and transcriptomics data. Environment and Opportunity: • A highly functional and collaborative research environment at the intersection of biology, chemistry, and machine learning. • Access to high-quality imaging datasets, state-of-the-art technologies, and pioneering research. • Participation in seminar series featuring academic and industry scientists. • Campus-like lifestyle with a healthy work-life balance. • Mentored opportunities for career development. Key Responsibilities • Curating, organizing, and manipulating imaging and transcriptomics data from various sources • Implementing deep learning frameworks, experimental design, model performance/evaluation, and visualization of results • Collaborate with scientific stakeholders to develop models and communicate results/recommendations • Lead technical discussions and present key findings for internal meetings Program Highlights • Intensive 12-weeks, full time (40 hours per week) paid internship. • Program start dates are in May/June (Summer) • A stipend, based on location, will be provided to help alleviate costs associated with the internship. • Ownership of challenging and impactful business-critical projects. • Work with some of the most talented people in the biotechnology industry. Who You Are (Required) Required Education: • Must have attained a Bachelor’s degree • Currently pursuing a Master’s or PhD degree (enrolled student) Preferred Majors: • Pursuing a degree in Computational Biology, Bioinformatics, Cheminformatics, Bioengineering, Computer Science or relevant engineering or scientific field. Required Skills: • Applied experience with machine learning and an understanding of deep learning pipelines • Strong python programming skills • Excellent analytical and problem-solving skills with a desire to learn new methodologies • Excellent communication, collaboration, and interpersonal skills Preferred Qualifications • Track record of applying AI platforms, technologies, and techniques (e.g. Pytorch, Tensorflow, scikit-learn…) to solve scientific problems • Previous experience with Pytorch and familiarity with AI developer platforms such as Weights and Biases • Experience with data visualization tools for scientific communication • Passionate about solving technical problems and applying novel technologies to further scientific discovery • Experience working in teams and collaborating with others to solve challenging problems Relocation benefits are not available for this job posting. The expected salary range for this position based on the primary location for this position in California is $22.00 - $55.00 per hour. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits. #GNE-R&D-Interns-2024 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