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Geisinger Health System: Computational Graph Theory, Postdoc

Geisinger Health System: Computational Graph Theory, Postdoc

At: Geisinger Health System

Location: Danville, PA

Web: www.geisinger.org Job summary:

Geisinger Division of Applied Research and Clinical Informatics (DARCI), Department of Data Science is seeking a postdoctoral researcher with a strong background in applied mathematics or computer science, with focus in computational graph theory and active interest in biomedical data analysis.

This position is supported by a 3-year grant "Integrating Big Data for Biomedical Discovery: Methods, Tools and Applications", a joint Geisinger/PSU research effort in development of algorithm and methodologies for data integration and analysis, with applications to treatment of obesity and obesity-related comorbidities, a health problem of critical concern to the Commonwealth of Pennsylvania.

In preliminary studies, we have developed graphical representations of complex heterogeneous data including clinical interactions, progression of the condition, and individual characteristics of patients. A postdoctoral specialist will perform research and development on medical data represented as graphs.

This position offers an opportunity for an early career mathematician/computational scientist t to develop into a multidisciplinary specialist with exposure to medical data and research workflow of a healthcare organization.

Duties and responsibilities:

  • Interact with subject matter experts to define the contents and metrics of proximity of graphs representing medical data
  • Write robust code for construction of graph representations of medical data
  • Implement summarization/visualization/validation on graphs.
  • Develop algorithms for clustering, coarsening/refinement, feature detection, optimization on graphs
  • Contribute to academic publications in medical informatics, with focus on personalized medicine and obesity studies.

General requirements:

Besides academic coursework and practical experience in computational graph theory, a qualified candidate should have general familiarity with methods and tasks of predictive analytics/machine learning, statistics and numerical optimization methods. Some direct experience with spectral methods in graph analytics is favorable.

Preferences for a candidate also include:

  • Experience in submitting research material to professional conferences, journals.
  • An interest in working collaboratively in a team of physicians, computer scientists, and programmers.
  • Positive and enthusiastic attitude.
  • Fluency writing and speaking the English language.

Software/programming requirements:

  • Experience with standard scientific computing languages: Matlab, R, Python, Sage, SPSS, SAS
  • Experience with some of the commonly used programming languages, including scripting languages : C++, Java, Ruby, Perl

Educational requirement:

Ph.D. is required ; a year or more of postdoctoral research experience are preferred.

Work status:

An applicant must be approved to work in the United States; we will consider extremely qualified applicants in need of visa support.

_Contact_:

Apply online here

or apply online at geisinger.org/careers , Other Opportunities, JOB ID 28415 .

Contact: Heather Lazo, hllazo@geisinger.edu , Recruiter, with questions.

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