Advanced Analytics Network Intern (Machine Learning/Image Processing)

United States of America, Arizona, Tucson

de fr es ru tr it pt zh ja

Roche is recruiting for a Machine Learning/Image Processing intern for six month, with flexibility to work part time or remotely depending on candidate's availability and business needs. Ideal candidates will begin internship in May 2020, however, flexibility in start/end dates can be accommodated.

Our intern will join various R&D teams across the organization and work on an innovative project applying advanced image processing and machine learning approaches to the company’s real world digital pathology datasets.

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 host team 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 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 or biomedical imaging data
  • Fluency in machine learning development environments (Pytorch, Keras, Tensorflow, etc.)
  • Experience with image data pre-processing techniques for algorithm training  
  • Strong communication and collaboration skills, particularly working with remote teams
  • Experience implementing reproducible research practices like version control (e.g. using Git) and literate programming
  • Demonstrated contributions to open source packages, libraries or functions
  • Desired hands-on experience with deep learning, multiple instance learning, and decision fusion techniques
  • Desired experience with technologies and techniques required for processing large data files, for managing large data sets, or with computationally intensive steps (e.g. parallelization, HPC cluster computing)

Qualifications:

  • Master's and PhD candidates or recent graduate in Image Processing and Machine Learning related field (e.g. Computer Science, Electrical Engineering, Biomedical Engineering, Medical Physics, Statistics/Biostatistics, or related disciplines)
  • Hands-on experience with designing training and validation datasets, statistical analysis, and machine learning techniques in the context of healthcare and image data
  • Proficiency with Python and/or MATLAB plus a deep learning environment (e.g. Keras)
  • Excellent communication and presentation skills
  • Able to work independently but also comfortable in a collaborative environment