We are looking for a highly motivated post-doctoral fellow to develop pattern recognition /computational models, algorithms and software tools to study (large-scale) unstructured longitudinal data in medical and health science including m-/e-health. The fellow should have strong computational skills in the areas of statistics (e. g. , Markov Models, Bayesian analyses) and data mining/machine learning. The fellow will participate in research dissemination activities. The fellow will work in collaboration with other members of the group, and will have the opportunity to work on multiple projects in a highly interdisciplinary setting with clinicians, statisticians, computer scientists, engineers, and mathematicians.
Candidates must have a PhD in (Bio)statistics, Bioinformatics, Computer Science, Engineering or a closely related field. Experience with statistical/computational/math ematical modeling and simulations is preferred. Prior experience in pattern recognition and experience with extracting and manipulating large data sets from various databases, and integration of these data into predictive computational models will be a plus.
Candidates should have strong programming skills in R, Matlab, SAS, C/C++ and/or Java and experience with algorithm design.
If interested, please send a cover letter, and CV to Dr. Hua Fang at Hua. Fang@umassmed. edu.
Working Title: Post Doctoral Associate
Requisition Number: 2014-22620
Exempt/Non-Exempt Status: Exempt
Union Code: Non Union Position-W63-Residents/Post Docs
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