Genentech is seeking an intern who is either pursuing or a recent graduate from a MSc/PhD degree with expertise in advanced analytics and machine learning to help us explore its potential applications in Alzheimer's disease. This intern will join various analytics teams in Early Clinical Development and work on an innovative project(s) applying advanced analytics and machine learning approaches to the company's imaging, observational study, and clinical trial data assets in Alzheimer's disease.

We are looking for individuals who are:

• Creative problem solvers, quick learners and comfortable experimenting with new approaches
• Demonstrate high productivity and enjoys dealing with ambiguity and applying novel methodologies
• Possess entrepreneurship, passion and curiosity for understanding and interrogating complex data.

Responsibilities:

• Collaborate with the clinical science, clinical imaging, and machine learning teams and other stakeholders to evaluate potential machine learning techniques and applications
• Design, build and interpret machine learning algorithms to address selected research questions (including preparing the input data)
• Proactively share learnings and knowledge to support the development of the wider Roche/Genentech Advanced Analytics community
• Help shape the direction of machine learning and artificial intelligence within Roche

Experience and Competencies Preferred:

• Knowledge of a wide range of machine learning techniques and applications Experience applying machine learning algorithms and techniques, preferably to healthcare data
• Experience with technologies required to undertake analyses on large data sources or with computationally intensive steps (SQL, parallelization, Hadoop, Spark, HPC cluster computing, Docker)
• Experience with imaging analysis would be beneficial
• Experience with clinical outcome measures for Alzheimer's disease would be beneficial
• Fluency in statistical programming languages (R, Python, etc.)
• Prior experience with deep learning and 1+ years of experience with a deep learning framework (Pytorch or Tensorflow)
• Prior experience with time series data
• Prior experience with RNN, LSTM , and transformer
• Strong communication and collaboration skills
• Experience implementing reproducible research practices like version control (e.g. using Git) and literate programming
• Demonstrated contributions to open source packages, libraries or functions Qualifications

Required:

• MSc/PhD degree candidate or recent graduate in Data Science related field (e.g., Statistics, Mathematics, Epidemiology, Health Economics, Outcomes Research, Computer Science)