The Ideker Laboratory is in the Division of Human Genetics and Precision Medicine at UC San Diego School of Medicine. We are a vibrant research team of 30-40 staff, postdocs, graduate students, and undergraduate students known for its dynamic and collaborative environment. We perform bioinformatics research coupled with wet-lab investigations, working in the areas of network biology, data-driven hierarchical modeling, and machine learning applied to biomedicine. We also support multiple open-source software projects, some with 100K+ users. One of the main research goals of the Ideker Lab is to create artificially intelligent, mechanistic models of cancer for translation of patient data to precision diagnosis and treatment. We are advancing this goal by developing "visible" predictive machine learning approaches to model the flow of genetic information to translate genotype to phenotype and, importantly, to identify the molecular functions and mechanisms by which these predictions are made.
The Ideker Laboratory is recruiting a Senior BioMachine Learning Scientist to lead machine learning R&D for the ADAPT project, a new precision cancer therapy initiative funded by ARPA-H. The overall goal of the ADAPT project is to use advanced AI/ML technologies to deliver the right therapy to the right patients at the right time. ADAPT will revolutionize cancer treatment by using predictive biomarkers and interpretable AI/ML to create dynamical cancer treatment strategies and personalized therapies for patients with metastatic cancers.
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Annual Full Pay Range: $119,400 - $230,800 (will be prorated if the appointment percentage is less than 100%)
Hourly Equivalent: $57.18 - $110.54
Factors in determining the appropriate compensation for a role include experience, skills, knowledge, abilities, education, licensure and certifications, and other business and organizational needs. The Hiring Pay Scale referenced in the job posting is the budgeted salary or hourly range that the University reasonably expects to pay for this position. The Annual Full Pay Range may be broader than what the University anticipates to pay for this position, based on internal equity, budget, and collective bargaining agreements (when applicable).
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