About the Job
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.
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.
- Work with and/or mentor 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.
Qualifications
Required Qualifications:
* 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 focuses on the 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.
Benefits
Working at the University
At the University of Minnesota, you'll find a flexible work environment and supportive colleagues who are interested in lifelong learning. We prioritize work-life balance, allowing you to invest in the future of your career and in your life outside of work.
The University also offers a comprehensive benefits package that includes:
- Competitive wages, paid holidays, and generous time off.
- Continuous learning opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program.
- Low-cost medical, dental, and pharmacy plans.
- Healthcare and dependent care flexible spending accounts.
- University HSA contributions.
- Disability and employer-paid life insurance.
- Employee wellbeing program.
- Excellent retirement plans with employer contribution.
- Public Service Loan Forgiveness (PSLF) opportunity.
- Financial counseling services.
- Employee Assistance Program with eight sessions of counseling at no cost.
How To Apply
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.
Diversity
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.
Employment Requirements
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.
