We seek a scientific programmer to join the agricultural data science initiative at the University of Arizona. Our team is responsible for developing automated pipelines for data collection, simulation modeling, and statistical analysis that integrate heterogeneous data with scientific understanding. The goal of this project is to develop plants that respond to environmental cues alongside new remote sensing methods that detect these responses.
The scientific programmer will work closely with scientists who collect, use, and analyze data to simulate and analyze the growth and ecological dynamics of engineered plants. The programmer will be responsible for the deployment, development, and execution of data analysis and land surface simulation models (such as BioCro, ED2, and/or CLM5) using the PEcAn (pecanproject.org) simulation modeling and analysis workflow software that integrates data collected from a variety of handheld, aerial, and ground-based sensor platforms.
The programmer will be expected to provide leadership in the development of new software and the adoption of best-practices in scientific computing, support analysis pipelines, learn new computing and current in fields of science and computing, to apply new knowledge to a cutting edge system, and to provide leadership in design and implementation decisions.
Duties and Responsibilities:
- Consult with collaborators and supervisor to understand and execute simulations.
- Work with team to organize, curate, publish, and use data and simulation model output.
- Develop, refactor, test, and document software.
- Gather feedback from collaborators to define software and analysis requirements and implement robust solutions that meet these needs.
- Develop and maintain technical and non-technical documentation.
- Work in an iterative, agile environment.
- Communicate with team.
- Master’s degree, or equivalent experience, in Computer Science, Math, or related fields AND strong science or engineering background
- PhD in ecological, geophysical, or related fields of science AND excellent skills in scientific computing.
- Experience programming in R OR Python and willingness to learn R.
- Demonstrated ability to adapt and learn new skills.
- Excellent organizational skills.
- Demonstrated ability to work collaboratively in a team.
- Experience working in a collaborative scientific research environment
- Experience with three or more of the following
- Relational Data with SQL.
- geospatial data and analysis.
- Plant Physiology, Ecophysiology, and Ecology
- Bayesian statistical analyses
- Simulation modeling.
- C, C++, or FORTRAN
- Version Control and Issue Tracking Software
Documents Needed to Apply
- Cover Letter
- CV or Resume
- Example Code or GitHub username
Apply Here: https://uacareers.com/postings/31668