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BACKGROUND

About TGen:
Translational Genomics Research Institute (TGen) is a Phoenix, Arizona-based non-profit organization dedicated to conducting groundbreaking research with life changing results. TGen is focused on helping patients with neurological disorders, cancer, and diabetes, through cutting edge translational research (the process of rapidly moving research towards patient benefit). TGen physicians and scientists work to unravel the genetic components of both common and rare complex diseases in adults and children. Working with collaborators in the scientific and medical communities literally worldwide, TGen makes a substantial contribution to help our patients through efficiency and effectiveness of the translational process. TGen is allied with City of Hope, a world-renowned independent research and cancer and diabetes treatment center. This precision medicine alliance enables both institutes to complement each other in research and patient care, with City of Hope providing a significant clinical setting to advance scientific discoveries made by TGen. For more information, visit: http://www.tgen.org.

Dr. Nicholas Schork, Director of Quantitative Medicine at TGen, seeks a creative, independent, and highly motivated researcher interested in computational and general quantitative aspects of health and clinical learning systems (i.e., systems that can be used to make predictions about intervention strategies for individual patients based on large clinical and outcome data sets). Clinical learning systems have the potential to radically transform the way health care is delivered and monitored and have their root in large-scale electronic medical record systems, artificial intelligence and machine learning techniques and clinical decision support strategies.

RESPONSIBILITIES

The post-doctoral fellow will have the opportunity to develop and evaluate health learning systems in a collaborative environment that includes basic scientists, computational and quantitative scientists, informaticians and clinicians, including those at TGen's affiliated institution, the City of Hope Hospital in East Los Angeles, as well as its many other partner institutions.

Learning systems in health care contexts take advantage of large amounts of data on patients (e.g., from Electronic Medical Records (EMRs)) to build predictive models that can be applied to future patients to determine sensible, if not optimal, courses of action based on their characteristics (e.g., genetic profile, past medical history, etc.). Such systems can be updated in real time given the continual patient accrual in clinical care settings. The design and implementation of such systems is receiving greater and greater attention, but present a number of challenges. For example, how can one harmonize relevant data in real time? What statistical analysis techniques should be used to develop the predictive models (e.g., deep learning)? How can such systems be coordinated across clinical entities to leverage even more data? The research questions and activities to be pursued in these contexts include:

Modeling and simulating the behavior of real-time clinical learning systems
Developing reliable, beyond state-of-the-field data-based analytic methods for guiding clinical decisions
Comparing different machine learning and statistical predictive analytic methods for their flexibility, robustness and reliability on simulated and real data
Developing strategies to integrate a wide variety of data types (e.g., genomics, imaging, wireless devices, etc.)
Beta-testing the implementation of novel systems with potential industry and academic partners
Helping oversee the implementation of systems and consulting on any issues that arise
Present findings on learning systems at major conferences and in peer-reviewed publications

TGen has access to some of the largest and fastest computing systems in the world that can be leveraged in the proposed research. In addition, the development of health learning systems will likely have a broad, international impact, so the research to be pursued will be highly visible and competitive and as a result could propel the career of an independently-minded researcher looking to impact others on a large scale.

REQUIREMENTS

Ph.D. (completed or near completion) in Computer Science, Operations Research, Informatics, Statistics/Biostatistics, Mathematics or a related field.
Exceptional computer programming skills
Familiarity with state-of-the-field machine learning and statistical analysis techniques
Experience with large, heterogeneous data sets
Excellent written and verbal communication skills
Willingness to work in clinical decision-making settings
Willingness to travel when necessary to collaborating sites
No publication record is required, but a publication track record is preferred

HOW TO APPLY

If you are interested in seeing the most up to date job listings or to apply for this position, please go to https://www.tgen.org/careers-tgen/#.WdP3F39e6Uk and submit your resume for IRC13069. Please take a moment to read about our employee benefits and learn more about TGen. If you have any questions about the company or how to apply for a position, please contact hr[at]tgen.org.

Only resumes submitted through the TGen career website will be considered.

Discussion forums: Opportunity: Postdoctoral Fellow in Computational Medicine @ The Translational Genomics Research Institute -- Phoenix, AZ (US)

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