McGovern Medical School at UTHealth Houston, Department of Neurology, is seeking a data scientist with expertise in clinical informatics or neuroinformatics, as well as research interests focused on neurological diseases, to join the Texas Institute for Restorative Neurotechnologies (TIRN) as a Research-Track Assistant Professor.
The prospective candidate would be able to participate in neuroinformatics initiatives, engage in field-leading research, assist in developing grant proposals, and collaborate on and submit research findings for publication to advance scientific knowledge. Research expertise/knowledge, demonstrated by peer-reviewed publications in data science, biomedical informatics, machine learning, AI, and healthcare applications, is most preferred.
Position Key Accountability:
- Work independently and collaboratively on research projects that focus on developing and conducting quantitative and qualitative research in the areas of biomedical informatics, AI, and healthcare applications.
- Participate in committees at the school and university levels, contribute to the broader community, and help enhance curriculum for medical students, residents, fellows, and post-docs.
- Mentor post-docs and graduate student research assistants in research and development activities.
- Participate in, develop, and expand the scope of collaborative and funded program portfolios for the institution. Independent extramural funding is encouraged but not required.
- Assist the UTHealth Chief Data Scientist in strategic planning and operational activities across school and inter-institution collaborations involving health data.
Qualifications:
- Doctorate Degree (Ph.D.) in related research environment with verifiable publication.
- History of participation and contribution to extramural research funding activities.
- Outstanding research, interpersonal, and communication skills.
Preferred Qualifications:
- Expertise in using machine learning and AI technologies to address healthcare problems.
- Experience in utilizing information technology to manage and process data sets in conjunction with electronic health records, particularly in the context of creating a data ecosystem and for domain-specific disease registries and repositories.
- Background in neuroinformatics, ontologies, and large-scale data.
