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 clinical, molecular and imaging datasets to extract insights, and drive research opportunities.
• Design and prototype novel analysis tools and algorithms for predicting patient outcome and treatment response.
• Collaborate with product, science, engineering, and business development teams to build 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.

Required Qualifications:

• PhD degree in a quantitative discipline (e.g. computer science, biomedical informatics, machine learning, statistics, computational biology, applied mathematics, physics, or similar).
• 3+ years of relevant industry or postdoctoral experience.
• Outstanding analytical and problem solving skills, with a particular focus on understanding the intricacies of multi-modal medical data sets.
• Experience working with clinical, electrocardiography, genomic, or imaging data.
• Expert-level experience with supervised, self-supervised and unsupervised machine learning algorithms, such as: regression, generative modeling, deep neural networks, gradient boosting, non-linear low dimensional embeddings and clustering.
• Proficient in Python and SQL.
• Experience with machine learning frameworks such as TensorFlow 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.

 Preferred Qualifications:

• Strong peer-reviewed publication record
• Familiarity with cloud computing services
• Experience building machine learning based models towards cardiovascular outcomes
• Experience working with structured and unstructured Electronic Health Records
• Experience with signal processing and modeling ECGs
• Familiarity with natural language processing 
• Experience in agile environments and comfort with quick iterations.

#LI-SH1

#LI-Hybrid

#LI-Remote

#LI-Onsite