Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Carnegie Mellon University
- Duke University
- Nature Careers
- University of Texas at El Paso
- George Mason University
- National Renewable Energy Laboratory NREL
- University of Massachusetts Medical School
- Auburn University
- Columbia University
- Cornell University
- Harvard University
- Pennsylvania State University
- The University of Chicago
- The University of Iowa
- University of North Texas at Dallas
- University of Texas Rio Grande Valley
- University of Texas at Austin
- 7 more »
- « less
-
Field
-
. Programming experience in Python. Excellent communication skills and fluency in English. Collaborative personality with attention for detail. Bonus but not required Experience with training and validating
-
packages and tools (e.g., Numpy, Pytorch, Tensorflow, ART). You have knowledge or familiarity with reverse engineering tools (e.g. NSA Ghidra, IDA Pro) You have experience with Python, C/C++, or low-level
-
Proficiency in Python programming is preferred Salary Commensurate with experience. Number of Vacancies Multiple Desired Start Date 06/01/2026 Posting Detail Information EEO Statement It is the policy
-
experience with new IBR models (e.g., WECC REGFMA1, REGFMB1, vendor-provided models) is a plus. Experience with software development in Python, C++, or other programming languages. Hands-on experience
-
Qualifications Education: ABD status by start date. PhD by start date in a field relevant to the research being conducted. PhD after one year of employment. Technical Skills or Knowledge: Proficiency in Python
-
tools (e.g., Numpy, Pytorch, Tensorflow, ART). You have knowledge or familiarity with reverse engineering tools (e.g. NSA Ghidra, IDA Pro) You have experience with Python, C/C++, or low-level programming
-
packages and tools (e.g., Numpy, Pytorch, Tensorflow, ART). You have knowledge or familiarity with reverse engineering tools (e.g. NSA Ghidra, IDA Pro) You have experience with Python, C/C++, or low-level
-
programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic applications, agricultural monitoring and modeling, Agro-AI/ML, or digital twin. Instructions
-
learning models, and willingness to learn about new methods, is a plus. · Strong programming skills in Python, and Linux Shell; experience in developing methods as open source repositories at e.g. GitHub is
-
Science. Commitment to undergraduate and graduate education. Demonstrated expertise in machine learning/deep learning and software development (Python; PyTorch/TensorFlow). Peer-reviewed publications and strong