Working Title:

Assistant/Associate Professor - Sequential Decision Making

Department:

Statistics IANR-0832

Requisition Number:

F_210219

Posting Open Date:

12/07/2021

Application Review Date: (To ensure consideration, please submit all application materials before review date):

01/17/2022

Open Until Filled:

Yes

Description of Work:

The incumbent will develop a high-impact, nationally and internationally recognized research and teaching program in sequential decision making in response to real time data collection. Example data sources include sensors or other automated observational data systems.

Research: Create new techniques (Bayesian, frequentist, computational, etc.) to extract the maximum value from data streams generated for the management of agricultural and natural resource systems. The incumbent is expected to collaborate with current faculty in both the agricultural/natural resource sciences and the computational/statistical sciences. This includes developing and deploying techniques and system strategies to acquire and prepare raw data in an analysis-ready form, ii) advising on system design, iii) developing techniques for analyzing data to make optimal sequential decisions, iv) seeking internal and external support, v) publishing in high-quality, high-impact peer-reviewed journals, and participate in scientific meetings and other appropriate professional activities, and vi) preparing students for the workplace by providing instruction in these emerging systems and techniques. Research duties for this position include field work with extension teams, subject matter experts and other partners.

Teaching: Support the statistics and data science degree programs to recruit, fund, and train undergraduates and graduate students. The normal teaching load is three courses per academic year; specific teaching assignments may change according to program needs.

The incumbent is expected to accept committee assignments, reporting responsibilities, and other special ad hoc assignments as requested at the administrative unit, college/division, institute, and/or university levels.

Recognizing that diversity within a context of inclusivity enhances creativity, innovation, impact, and a sense of belonging, the Institute of Agriculture and Natural Resources (IANR) and Animal Science are committed to creating learning, research, Extension programming, and work environments that are inclusive of all forms of human diversity. We actively encourage applications from and nominations of qualified individuals from underrepresented groups.

As an EO/AA employer, qualified applicants are considered for employment without regard to race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See http://www.unl.edu/equity/notice-nondiscrimination.

Minimum Required Qualifications:

• Ph.D. in statistics, data science, engineering, or closely related field.
• Written work in sensor data analysis, sequential decisions, streaming/observational data or closely related areas.
• Computational proficiency such as coding or algorithm design.

Preferred Qualifications:

• Demonstrated practical experience in statistics, data science, engineering in a related field of importance to IANR.
• Excellent communication skills.
• Ability to engage in scientific teamwork to address major issues.
• Teaching experience at the university level.
• Interest in working with diverse or underrepresented communities or groups.

How to Apply:

Click “Apply to this job” and complete the information form. Attach the following documents:

1. A letter of interest that describes your qualifications for the job, anticipated contributions, and the value you place on diversity and your anticipated contributions to creating inclusive environments in which every person and every interaction matters (2 page maximum; see https://ianr.unl.edu/tips-writing-about-commitment-to-deib for guidance in writing this statement).
2. Your curriculum vitae.
3. A teaching and research statement (1 page each). Combine into one document and attach as “Other Document."
4. Contact information for three professional references.

For questions or accommodations related to this position contact:

Leonita Masek
lmasek2@unl.edu

Job Category (old):

Faculty Tenure/Tenure Leading

Job Type:

9 Month

Position funded by grant or other form of temporary funding?:

No