Computational Text Analysis Faculty in UCSF Institute for Computational Health Sciences
Assistant level Professor
UCSF Institute for Computational Health Sciences
The Institute for Computational Health Sciences (ICHS) at UCSF is looking to recruit a computational text analysis faculty member at the Assistant Professor level. ICHS is seeking faculty candidates with a strong background in natural language processing (NLP) who have an interest in clinical informatics, machine learning, and/or network/mathematical modeling as applied to health research. Candidates are required to hold a doctorate in informatics, computer science, epidemiology, biostatistics, or a related discipline with demonstrated experience/expertise in advanced analysis of text-based information and NLP, and/or a medical, dental, nursing or pharmacy degree with demonstrated experience/training in NLP as well as having demonstrated significant achievement or promise in their field. A primary affiliation with ICHS will be provided, along with an academic appointment within a department closely allied with the applicant’s scholarly or clinical expertise. The appointee will be expected to build collaborations with faculty across campus in efforts to advance the field of text analysis/NLP at the University, to develop and deliver text analysis/NLP curricula to a wide campus audience including students, staff, and trainees, and to mentor graduate and medical students while developing extramurally-sponsored research programs.
About the Institute:
The Institute for Computational Health Sciences (ICHS; ichs.ucsf.edu) is a critical component of a global UCSF initiative in Precision Medicine, which seeks to aggregate and integrate vast, disparate datasets to advance understanding of biological processes, determine mechanisms of disease, and inform diagnosis, prevention, and treatment. Since its formation in 2015, ICHS has established a cohort of 49 affiliated faculty who represent a diverse array of departments drawing from UCSF’s four top-ranked professional schools (Dentistry, Medicine, Nursing and Pharmacy) and Graduate Division; and whose talents are evidenced by a host of honors including 5 National Academy of Medicine members, a National Academy of Sciences member, 2 members of the American Society for Clinical Investigation, 3 NIH Director’s Awards, 2 Sloan Foundation Fellows, an HHMI Faculty Scholar, and MacArthur Foundation Fellow. ICHS investigators employ computational strategies in basic, translational, clinical and population-based biomedical research within the interest areas of biological modeling, precision oncology, clinical informatics, computational neuroscience, computational pharmacology, deep machine learning and data visualization, population precision medicine, and very large data molecular measurements (two featured as Genome Advance of the Month by the National Human Genome Research Institute).
We foster collaborations within the UCSF Medical Center, named among the nation’s premier medical institutions for 15 consecutive years, as well as the statewide UC system, including 5 academic medical centers (Davis, Irvine, Los Angeles, San Diego, San Francisco) comprising UC Health. As Executive Director of Clinical Informatics for UC Health, our ICHS Director works to ensure the integration of all UC Health data into an accessible Clinical Data Warehouse representing more than 15 million patients, and supports our investigators in their efforts to transform this unparalleled wealth of information into advancements in knowledge to improve health.
UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.
Please apply online at http://apptrkr.com/1173291.