Assistant Director - Research
A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
The Michigan Institute for Data and AI in Society (MIDAS) seeks an Assistant Director - Research to oversee our research programs and some components of our training programs, and to carry out research support activities. MIDAS is an organization under the University of Michigan Office of the Vice President for Research. Our mission is to advance research in data science and artificial intelligence (AI), and enable their transformative use in a wide range of research disciplines to achieve lasting scientific and societal impact. We lead strategic thrusts in data science and AI research; enable collaborative grants, provide research training, and build research resources. Through these approaches, we facilitate the development of cutting-edge methods and the application of these methods to important problems in all research disciplines. We foster a world-class data science and AI research community at U-M. We also build coalitions with academia, industry, government and the community, and support the use of data and AI for positive societal impact. This person will report to Dr. Jing Liu, MIDAS Executive Director, and will collaborate closely with the Assistant Director - Operations.
Managing research programs and a portion of the training programs and staff members:
- Design and implementation of research incubation activities to enable research collaboration and grants.
- Manage the pilot grant program.
- Design and implementation of AI exploration, online resources and consultation programs.
- Design and implementation of AI tool development for research capacity building.
- Content development for research training, including the summer academies and AI tutorials.
Research support. Together with other staff scientists:
- Develop resources that improve the research capacity across research domains, including guidelines and technical tools.
- Facilitate the development of innovative research ideas and teams, including consultations for research projects;
- Develop and deliver technical training for faculty and other researchers.
- Other research activities, including participating in research proposals and projects.
Assist the Executive Director in collaboration development, grant proposal development and fundraising.
Communication and Administrative:
- For MIDAS research and related activities, collect data and assist in evaluation in order to assess program effectiveness, develop content for reports.
- Develop scientific content for website and newsletter, promotional materials and other forms of dissemination.
Required Qualifications
- PhD degree in a quantitative field;
- More than 3 years of post-graduate research experience with one or more essential data science and AI methodologies, for example:
- Databases and data management;
- Software engineering;
- Machine learning;
- Natural language processing;
- Modern statistical methods.
- More than 2 years of post-graduate experience in managing research groups and collaborative projects.
- Professionalism, strong work ethic, demonstrated sense of responsibility, discretion and reliability.
- Ability to set priorities, exercise initiative, solve problems, adapt to changes quickly, make independent judgments, and work effectively both independently and collaboratively as part of a team.
- Excellent written and verbal communication skills; timely and consistent communication and follow-through with the leadership, the team and stakeholders.
- Strong interpersonal skills and the ability to drive consensus.
- Strong organizational skills and attention to detail.
Preferred Qualifications
- Experience engaging with highly technical researchers across a variety of methodological fields, research domains, and computational platforms.
- Broad interest in data science and AI and their application domains.
- Teaching experience in data science and AI.
- A track record of productive research, reflected in publications, projects, and current and past collaborations.
- Familiarity with the U-M research environment.
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