- Texas A&M Institute of Data Science
Texas A&M University
Blocker Bldg, Rm 143
College Station, TX 77843-3143
| Position ID: | Texas A&M University-Texas A&M Institute of Data Science-REIII [#20535, R-043809] |
| Position Title: | Research Engineer III |
| Position Type: | Other |
| Position Location: | College Station, Texas 77843, United States [map] |
| Subject Areas: | Agriculture / Computation Data Science / data analytics |
| Appl Deadline: | (posted 2021/11/16, listed until 2022/04/22) |
| Position Description: |
| Who We Are: The advent of advanced instrumentation, detailed environmental data, and precision treatment capabilities in agriculture, provides new and compelling opportunities to apply Data Science to Agricultural Engineering. Texas A&M’s Department of Electrical & Computer Engineering, the Department of Visualization, AgriLife Research, AgriLife Extension, and the Texas A&M Institute of Data Science (TAMIDS) collaborate in a cross-disciplinary research program that integrates across foundations and practice by (i) using machine learning techniques to model the influence of plant genetics, the environment, and treatment factors on plant growth; (ii) developing algorithms that adaptively optimize treatment over the growing season to meet goals for yield and cost; and (iii) embodying these algorithms in decision support systems that can deliver practical recommendations for crop treatment based on available knowledge. What We Want: We seek a Research Engineer III who can integrate vertically across machine learning and AI, high performance computing, and data management, to design and produce prototype expert systems which also incorporate interfaces to support user queries and visualization. The position should appeal to someone with a broad set of systems, computing, and Data Science skills who enjoys harnessing state-of-the-art analytic methods to have practical impact in agricultural practice. The initial focus of work concerns development of efficient schedules for crop irrigation, specifically to develop an Unmanned Aerial System (UAS)-based crop monitoring system that models crop water use for irrigation scheduling and increased water use efficiency, based on UAS-derived phenotypic data and infield weather data. Responsibilities:
Preferred Education:
Appropriate PhD degree Required Experience:
Four years of related experience Preferred Experience:
Preferred special knowledge, skills and abilities:
All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution’s verification of credentials and/or other information required by the institution’s procedures, including the completion of the criminal history check.
Equal Opportunity/Affirmative Action/Veterans/Disability Employer committed to diversity. |