The University of Cincinnati Division of Cardiovascular Health and Disease is calling applications for a Post-Doctoral Fellowship. This position is to support a large multicenter clinical trial — Critical Health Assessment and Outcomes Study (CHAOS) which employs a multidisciplinary approach for optimization and validation of numerical algorithms for dynamic predictive monitoring for early diagnosis of critical illness.
This position requires:
- Strong software programming, data structuring, compiling, debugging and design skills, including the ability to translate (recode) existing Matlab software into C/C++, CUDA and Python.
- Developing new signal processing algorithms and optimizing existing algorithms and patterns or shapes in time-series data from animal models and human subjects.
- Enhancing existing systems by analyzing objectives, preparing an action plan and identifying areas for modification and improvement in “big data” informatics, network engineering and electronic health record queries for the design of embedded products, including code/compiler optimizations.
- Solving complex problems in clinical medicine through a collaborative effort with biomedical scientists, IT staff, engineers, statisticians, mathematicians, physicists and clinicians.
- Coordinating and assuming primary responsibility for all IT/engineering aspects, including (1) maintaining standard operating procedures and guidelines; (2) assuring compliance with applicable state, federal, and institutional laws/regulations pertaining to animal and human research; (3) general upkeep of hardware and software functionality; (4) training/guiding students/staff.
- Maintaining experimental data/records and sharing these with the PI in weekly meetings and presenting research results orally and in writing through conference and journal article publications
The incumbent on this Post-Doctoral Fellowship at the University of Cincinnati will be an engineer who will be responsible for prototyping new features, contributing to the overall design and architecture of future components and improving existing codebases, including:
- Developing and optimizing tools for automated and secure storage of physiological waveform data from telemetry and remote monitoring of patients for linkage with the electronic health record.
- Collecting, processing and analyzing data from large, multicenter randomized clinical trials.
Using this information to develop and validate numerical algorithms for predictive monitoring using real-time stream-computing and high-performance computing.
- Creating an open-source open-platform informatics/analytics infrastructure freely available to the research community for translating Big Data science into clinical practice.
In order to apply for this Post-Doctoral Fellowship at the University of Cincinnati, applicants must have
- B.S., M.S. or Ph.D. in Computer Science, Computer Engineering, Biomedical Engineering or related field, and 3 years of related experience are required; and publications in a related field preferred.
- Knowledge and experience developing pattern recognition and machine learning algorithms, signal processing, parallel programming, and software development for “Big Data” analytics are preferred.
- Strong coding skills with software and tools including Matlab, C/C++ and CUDA are necessary.
The University of Cincinnati (UC or Cincinnati) is a public research university in Cincinnati, Ohio. Founded in 1819 as Cincinnati College, it is the oldest institution of higher education in Cincinnati and has an annual enrollment of over 44,000 students, making it the second-largest university in Ohio. It is part of the University System of Ohio, with four major campuses. Cincinnati’s main campus and medical campus are located in Clifton Heights, while its branch campuses are in Blue Ash and Clermont.