Additional Verification Required
Health AI and Data Scientist (Researcher 6)
Job Description
- Graduate/Advanced Degree in computer science or related quantitative field and a minimum 2 years of experience post-graduation applying ML for natural language processing, preferably in a health-related field, with substantial research and publication record
- Strong background in natural language processing techniques and frameworks
- Strong background in applied statistics (e.g. Bayesian inference, regression, causal inference, survival analysis).
- Demonstrated ability to effectively communicate both verbally and in writing, to communicate ideas clearly and prepare scientific manuscript methods and results
- Excellent data visualization skills
- Familiarity with using statistical tools to analyze structured data and perform hypothesis testing
- Ability to function well in a fast-paced research environment, well organized, self- motivated to set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs
- Work well in diverse teams, as well as independently, to partner effectively with multiple groups across several organizations
Preferred Qualifications:
- Research experience in biomedical natural language processing, knowledge graph embedding, predictive modeling on longitudinal data, computer vision, and/or causal
inference.
- Expertise in transformers, reinforcement learning, transfer learning
- Experience leading projects within a research team
- Working knowledge of modern web service and/or software implementation
- Ability to work collaboratively with a diverse group of research scientists with different skill sets and expertise
- Strong experience with preparing peer-reviewed publications
About the Division/Department/Center/Program
The Division of Computational Health Sciences is a division which focuses on development of novel computational and AI methods to analyze biomedical big data for advancing health care.
The division currently has 8 faculty members and over a dozen research trainees. The department of Surgery (DOS) is driven to deliver clinical excellence, compassionate patient
care, pioneering research, and the education of surgical leaders. The DOS has a rich history of renowned basic and clinical science research, distinguishing itself as an academic and clinical
center of excellence. The 2023 NIH Blue Ridge Ranking is #4 among all Surgery departments in the nation.
The Center for Learning Health System Sciences is a one-of-a-kind partnership between the Medical School and School of Public Health with a goal to decrease the time it takes for science
to make it from the lab to the clinic in pursuit of better health outcomes for the patients we serve. CLHSS is composed of a core and five programs spanning the data-knowledge-practice
LHS lifecycle including evidence synthesis, pragmatic trials, digital health, and data democratization and model development. CLHSS is committed to diversity, equity, and
inclusion in its staffing, operations, and research. Learn more about the center by visiting: med.umn.edu/clhss
Summary of Position:
The Division of Computational Health Sciences (DCHS) at Department of Surgery and the Innovative Methods and Data Science Program within the Center for Learning Health System
Sciences (CLHSS) at the University of Minnesota are jointly seeking a full-time experienced data analyst to support multiple projects in the field of natural language processing (NLP), clinical
artificial intelligence (AI), machine learning (ML), and statistics. The successful candidate will closely work with the DCHS and CLHSS faculty and team members on cutting-edge research
projects using real-world patient big data and collaborate with teams in M Health Fairview and other external institutions and health systems. The responsibilities of the analyst will be to develop, test, and train AI/ML models using both image, unstructured text, and structured electronic health record (EHR) data, create analytical datasets to support observational
research studies, maintain supporting documentation related to programming, assist with statistical analyses, and provide quality assurance related to the storage and acquisition of new data. IMDS currently consists of faculty members, students, and staff from computational health sciences, biostatistics, computer science and health informatics with interdisciplinary expertise.
Duties/Responsibilities:
- Regularly conduct computational experiments to execute machine learning and deep learning algorithms on various data projects, with a specific focus on NLP tasks – 50%
- Assist with new project development including topic refinement, study design, data collection/cleaning, etc.
- Design and/or implement AI and other novel methods (e.g, LLM and multimodal models) for analyzing healthcare data , summarize findings, and generate study results for research topics
- Work under general supervision but has the discretion to make daily operational decisions on assigned projects; decisions may involve identifying the best
approach from alternatives and integrative solutions, determining how to best use available resources, recommending novel or new approaches. - Working and/or mentoring team members to conduct research projects,
disseminate research findings and explore new projects
- Support IMDS program of CLHSS – 50%
- Create analytical datasets to support observational research studies.
- Mentor and train undergraduate and graduate computer science and data science students.
- Actively participate in program and center meetings and events.
- Help define and implement shared best practices and process flow across related CLHSS programs and partners.
- Disseminate project results and findings through publication and presentations.
Committed to innovation and diversity, the Medical School educates physicians, scientists, and health professionals; generates knowledge and treatments; and cares for patients and communities with compassion and respect. We value excellence, inclusiveness, collaboration, and discovery.
Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online application for the position and attach a cover letter and resume.
Additional documents may be attached after application by accessing your “My Job Applications” page and uploading documents in the “My Cover Letters and Attachments” section.
To request an accommodation during the application process, please e-mail [email protected] or call (612) 624-8647.
The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.
The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu
Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.
The University of Minnesota, Twin Cities (UMTC)
The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.
At the University of Minnesota, we are proud to be recognized by the Star Tribune as a Top Workplace for 2021, as well as by Forbes as Best Employers for Women and one of America’s Best Employers (2015, 2018, 2019, 2023), Best Employer for Diversity (2019, 2020), Best Employer for New Grads (2018, 2019), and Best Employer by State (2019, 2022).
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