Job Description

University of Minnesota Institute for Health Informatics Faculty Position in Natural Language Processing/Knowledge Representation/Relational Data Modeling (Tenure/Tenure Track)

The Institute for Health Informatics (IHI) at the University of Minnesota (UMN), Twin Cities, invites applications for one or more open rank positions (tenure/tenure track) with specialized expertise in the Biomedical Artificial Intelligence areas of Natural Language Processing, unstructured data modeling, and knowledge representation.

The IHI is an institution-wide Institute with 21 core faculty, 65 affiliate faculty, 3 graduate (MS, MHI and PhD) programs with 80+ students and several joint and affiliate educational programs. IHI faculty lead investigator-initiated projects in the areas of Clinical Informatics, Translational Bioinformatics, AI for Healthcare improvement, Precision Medicine Informatics, Predictive and Causal Machine Learning, and NLP. They engage in numerous collaborative proposals across the UMN 6 Health Sciences Schools and across the disease spectrum. Several NIH-funded centers and state-wide initiatives are led, co-led or substantially supported by IHI faculty including major efforts in computational psychiatry, longevity/aging science, Cancer Research to name a few areas. The sister CTSI Health Informatics Program provides access to substantial institutional and external data used for research as well as extensive data management, consulting and collaborative science infrastructures and connectivity to collaborators across the translational spectrum.

The IHI has a strong track record in NLP method development and applications in EHRs including multiple NIH-funded investigators in this area. We seek to expand our faculty capacity and capability in the following AREAS of FOCUS:

• Biomedical NLP using Deep Learning, causal inference and other forward looking methods.
• Biomedical Knowledge Representation and Reasoning including computable guidelines, biological pathway modeling and induction from literature, computational models of cognitive
  decision making.
• Analysis of relational database, citation/literature, social media, and other analysis and
  modeling of unconventionally-structured data.
  

This is an open-rank search including:

• Junior faculty to be appointed as tenure track Assistant Professors. Successful candidates will have formal doctoral-level training in AI, Computer Science, Computational Linguistics,  LP or related discipline with extensive training in the health sciences. They should have early career accomplishments (methodological innovations, publications, early career grants) that suggest high likelihood of making significant and nationally-impactful contributions in their field of study.
• Mid-career or senior faculty to be appointed as tenure-track/tenured Associate or tenured Full Professors. Successful candidates will have formal doctoral-level training in AI, Computer Science, Computational Linguistics, NLP or related discipline with extensive training in the health sciences. They should have significant and nationally-impactful career accomplishments (major methodological innovations, applications, publications, funding record) that suggest high likelihood of sustained and expanding nationally-impactful contributions and thought leadership in their field of study.

The successful faculty candidates will be expected to:

• Develop and lead a research program of enduring scientific impact in the above AREAS of FOCUS.
• Participate in student and junior faculty mentoring and teaching in IHIâ™s graduate programs.
• Participate in various service and shared governance committees and activities.
• Faculty candidates with appropriate backgrounds can also have cross-appointments in related fields to help facilitate research program development and teaching endeavors.

About University of Minnesota Twin Cities

The University of Minnesota, founded in the belief that all people are enriched by understanding, is dedicated to the advancement of learning and the search for truth; to the sharing of this knowledge through education for a diverse community; and to the application of this knowledge to benefit the people of the state, the nation, and the world.

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