Successful applicant will be part of an interdisciplinary team that develop and apply computational methods and databases to analyze large-scale human cancer clinical data and genetic data in electronic medical records (EMR) to better understand treatment responses and clinical outcome in cancer patients in order to guide personalized cancer therapy. Successful applicant may also play a role in developing systems for integrating novel informatics tools and methodologies into clinical practice.
Develop and implement text mining methods and tools to analyze unstructured oncology EMR data including imaging reports, pathology reports and progress reports.
Deep expertise in NLP methods and tools.
Prior experience analyzing electronic medical record or electronic health record data.
Deep expertise in supervised, unsupervised and semi-supervised machine learning methods, with extensive experience in key open source software resources in these domains.
A track record of leading biomedical projects using statistical or computational approaches
Outstanding programming skills in Python, Perl, R, and/or C++
Strong knowledge of Unix shell scripting
Strong communication and writing skills
A proven track record of scientific publication in the fields of machine learning, deep learning, and/or natural language processing.
Contact Rong.Chen@sema4.com