Here at Tempus we believe the greatest promise for the detection and treatment of cancer and other diseases lies in building a deep understanding of the interaction between molecular and imaging attributes and clinical treatment.
We're on a mission to redefine how genomic and imaging data are used in a clinical setting. We are looking for Computer Vision Scientist who are passionate about the prospect of building the most advanced data platform in precision medicine.
What You'll Do
Research and development of novel imaging data based machine learning algorithms for the product platform
Apply statistical and machine learning methods to analyze large, complex data sets
Communicate highly technical results and methods clearly
Interact cross-functionally with a wide variety of people and teams
PhD degree in a quantitative discipline (e.g. statistics, statistical genetics, imaging science, computational biology, computer science, applied mathematics, applied physics or similar) or equivalent practical experience
Experience developing, training, and evaluating deep-learning models using public deep learning frameworks (e.g. PyTorch, TensorFlow, and Keras)
Experience developing, training, and evaluating classical machine learning models, such as linear and logistic regression, SVMs, Random Forests, and Gradient Boosting
Familiar with CUDA and GPU computing
Knowledge of different medical imaging modalities, DICOM formats, and/or pathology images
Self-driven and work well in an interdisciplinary team with minimal direction
Thrive in a fast-paced environment and willing to shift priorities seamlessly
Nice to Haves
Kaggle.com competitions and/or kernels track record
Experience with AWS architecture
Experience working with survival analysis, clinical and/or genomic data
Experience working with Docker containers and cloud-based compute environments.
Familiarity with neural network techniques (batch-norm, residual connections, inception modules, etc).