Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
What You Will Do:
- Analyze and integrate large diverse cardiac clinical, molecular and imaging datasets to extract insights, and drive research opportunities and product development.
- Design and prototype novel analysis tools and algorithms for predicting disease onset, patient outcome and treatment response.
- Collaborate with product, science, engineering, and business development teams to build and bring to market, the most advanced data platform in precision medicine.
- Interrogate analytical results for robustness, validity, and out of sample stability.
- Document, summarize, and present your findings to a group of peers and stakeholders.
- Provide technical leadership & expertise across multiple modeling projects.
- PhD degree in a quantitative discipline (e.g. computer science, electrical/computer engineering, machine learning, bioinformatics, statistics, computational biology, applied mathematics, physics, or similar).
- 5+ years of relevant industry or postdoctoral experience.
- Outstanding analytical and problem solving skills, with a particular focus on understanding the intricacies of molecular or multi-modal data sets.
- Strong experience working with cardiac clinical and imaging data and applying AI to solve problems in cardiology.
- Expert-level experience with supervised and unsupervised machine learning algorithms, and ensemble methods, such as: PCA, regression, deep neural networks, decision trees, gradient boosting, generalized linear models, mixed effect models, non-linear low dimensional embeddings and clustering.
- Proficient in Python and SQL.
- Experience with the following: Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks, and a machine learning framework such as TensorFlow, SageMaker, or PyTorch
- Strong programming skills.
- Thrive in a fast-paced environment and willing to shift priorities seamlessly.
- Experience with communicating insights and presenting concepts to diverse audiences.
- Team player mindset and ability to work in an interdisciplinary team.
- Goal orientation, self motivation, and drive to make a positive impact in healthcare.
- Strong peer-reviewed publication record.
- Experience working in a Linux / Mac and AWS cloud environments.
- Experience in agile environments and comfort with quick iterations.
- Technical leadership experience.