Degree Level: Ph.D.

Major (s): Computer Science, Statistics

Duties/Tasks: Develop and apply advanced statistical methodology for analyzing sparse, and high-dimensional healthcare data.  Build on multivariate data-mining/machine-learning theory and methods for automatically inducing patient characteristics and disease progression from their medical records.  Develop and apply scalable and practical inference techniques for real-time analysis of patient health records. Develop methods for handling incomplete data in clinical studies. Employ aforementioned methods on large-scale clinical and survey data available at Bosch RTC.  Discover hidden patterns in patient health records to detect early warning signs for use in disease management.  Identify clinical decision rules for use in intention-to-treat epidemiology.  Identify and apply for relevant publicly funded research opportunities.  Publish in leading conferences and journals.

Knowledge and Skills:

• Ph.D. in Computer Science, Statistics or related fields
• Demonstrated expertise in machine learning, data mining, and analysis of experiments
• Strong programming experience in C++ (STL)/Java
• Experience with one or more of the following: Matlab/SAS/S-PLUS/R, SQL, and Python/Ruby/Perl
• Working knowledge in high-performance/distributed computing (MPI, MapReduce) is a plus