SimBioSys is a technology company on a mission to deploy Computational Oncology to transform decision making and patient experience in Cancer Care. By virtualizing cancer, clinicians and patients are empowered with a better understanding of the disease and can assess all available options computationally to truly individualize treatment.

We are seeking candidates who can contribute to the research and development of convolutional neural network (CNN) based methods for the analysis of medical imaging. You will develop state of the art models to virtualize the healthy and diseased tissue of individual cancer patients and gain new insights from other medical data domains including our own biophysical simulation.

The position will require you to work independently to design and improve upon deep learning assets. You will work closely with internal stakeholders, who are not deep learning subject matter experts, to build computer vision solutions for their medical imaging tasks. You will face technical challenges at SimBioSys which cannot be solved by cookie-cutter applications of common techniques. A successful candidate must be able to understand and stay abreast of the state-of-the-art in the field, implement new techniques based on their reporting in the literature, and develop novel approaches when appropriate. Fostering your analytical, biological, and computational skills, this position will provide you real world experience solving problems, while allowing you to contribute to the fight against cancer.

Requirements and Qualifications

  • Degree in quantitative discipline (e.g., Engineering, Computer Science, Mathematics, Physics, etc.)
  • Proficient in the Scientific Python stack including PyTorch
  • Experience with deep neural networks (CNN or other deep networks)
  • Experience with Computer Vision tasks, such as semantic segmentation or object detection
  • Experience collating and curating unstructured image data into datasets
  • Excellent written and verbal communication skills
  • Strong background in statistics
  • Ability to work independently and as part of a team to meet project goals

Desired Qualifications

  • Experience with advanced deep learning techniques (e.g., self-supervised learning, contrastive learning, generative modeling, etc.)
  • Experience with medical imaging (MRI, CT, PET, etc.)
  • Experience with DICOM
  • Knowledge of human anatomy