The Scripps Translational Science Institute (STSI), in close collaboration with the Todd Coleman Lab at UCSD is looking for an inspired, fun, and transformational-focused post-doctoral data researcher. In this position the fellow will work closely with clinical research teams from STSI and the machine learning experts at UCSD in designing and developing innovative and efficient analytical techniques and approaches to data-intensive clinical trials involving large volumes of personalized physiologic data. The successful applicant will be able to develop and implement novel analytical techniques meant to capture the time-varying dynamical nature of physiological data sets, with special considerations given to efficiency and scalability meant to deal with the growing size and complexity of data to be dealt with.
Additional duties will include guiding the development of the infrastructure necessary to optimize the integration of multiple sources of data to detect previously unknown and clinically meaningful changes and associations. The candidate is also expected to participate in the writing of manuscripts and creation of presentations describing the results of the research.
Position Qualifications and Requirements Experience/Specialized Skills
• Must have experience in developing sequential probabilistic models for describing and evaluating the time-varying dynamical nature of physiological data sets. Must also have experience developing efficient, scalable analytical methods while working with large, complex and multi-modal data sets. Must be able to work in a scientific team environment and have the ability to develop novel approaches in handling data- intensive clinical trials. Experience with state space modeling and estimation, convex optimization, and python programming are preferred.
Required Education/Courses/Training
•
PhD in Statistics, Biostatistics, Computer Science, Electrical Engineering, Operations
Research, Mathematics or related field
Interested candidates should pass on their CV to [email protected]