Principal/Senior Computational Biologist

Are you passionate about using clinical-genomics to transform cancer therapeutic care?

Tempus is a technology company at the forefront of the expansion of multi-modal healthcare data generation and the application of artificial intelligence (AI) to fundamentally change cancer care. Tempus is growing, and we are seeking exciting new talent to join the team.

Tempus' proprietary platform connects an entire ecosystem of real-world data to deliver real-time, actionable insights enabling physicians to drive better outcomes through precise, individualized care. Our data accelerates the pace of innovation, empowering researchers to characterize disease, discover new opportunities, maximize clinical trial success, and ensure the right therapies reach the right patients.

Excitingly Tempus is expanding. We are looking for a talented computational biologist skilled with genomics, systems biology and real world evidence to join our team. We are establishing a strategic alliance with a world leading biopharmaceutical company, and are assembling a team to drive this initiative to success. As a Tempus employee you will have access to the world’s largest real-world patient clinical data set linked to genetics, transcriptomics and digital pathology, alongside an extensive library of tumor derived organoids. Using Tempus’ data and platforms, you will deliver transformational impact across the entire drug R&D lifecycle. You will also develop methodology and algorithms advancing cancer precision medicine for patients across the Tempus network.

Responsibilities:

• Partner with a major pharma or biotech client to design, develop and execute computational research leveraging the Tempus platform to advance drug R&D programs.
• Become an expert in Tempus’ epidemiological, clinical, ‘omic and imaging data & tools.
• Become an expert in the pharma/biotech clients’ strategies, drug modalities and pipeline to identify where the Tempus platform can add value.
• Collaborate with the pharma/biotech client's scientific and technical teams to co-architect solutions and projects.
• Analyze multimodal big data to extract insights and drive new research opportunities, including new target discovery.
• Collaborate with Research, Engineering & Data Science teams at Tempus to develop and deliver innovative computational solutions.
• Document, summarize and communicate highly technical results and methods clearly to non-technical audiences.
• Drive continual improvement of the Tempus platform by communicating client feedback, staying ahead of research and industry trends, and championing new opportunities.
• Lead projects and mentor individual contributors to maximize impact.
• Author whitepapers and peer reviewed manuscripts.

Preferred Qualifications:

• Education
  • PhD, or Masters and 2 + years of experience
  • In addition to 6 + years of directly relevant work experience
  • Pharmaceutical/Biotechnology experience (either through employment or collaboration)
  • Management or multidisciplinary project team leadership experience
  • Education and experience must combine:
    • Quantitative and computational skills (e.g. Computational Biology, Biostatistics/Statistical Genetics, Bioinformatics, Biomedical Informatics, Biometrics, or Data Science for Health)
    • Biological or medical knowledge (e.g. Human Disease, Oncology, Genetics/Genomics, Molecular Biology, or Immunology)
• Comfort in a client facing role
• Proficient in R or Python packages for computational biology
• Experienced with SQL
• Strong understanding of the molecular nature of human disease
• Ability to deliver actionable insights from NGS, clinical and/or real-world data sets
• Competency in statistical and mathematical techniques for biological data analysis
• Expertise in one of the following:
  • target discovery
  • in vitro data analysis and phenomics
  • network and systems biology
  • mechanistic modeling and simulation
  • knowledge analytics
  • deconvolution and causal inference
  • integrative analysis of multi-modal data
  • real world evidence and survival analysis
• Thrive in a fast-paced environment and willing to shift priorities seamlessly.
• Experience in any of the following will also be beneficial: drug R&D; organoids and organoid data; clinical trial data; oncology; immunology; single cell or spatial transcriptomics; digital pathology; knowledge or graph based AI techniques; Bayesian networks and inference; image analysis; Digital twins; Clinical data standards; Clinical trial design and statistics; Biometrics

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