Postdoctoral Appointee – Machine Learning, Deep Learning, Computer Vision for Ecology

Argonne National Laboratory

Lemont, IL

Job posting number: #7064768 (Ref:407736)

Posted: February 21, 2020

Application Deadline: Open Until Filled

Job Description

The mission of Argonne’s Environmental Science Division (EVS) is to provide pioneering fundamental and multidisciplinary research and innovative analyses to solve global and local challenges, applying our core competency in predictive environmental understanding. Argonne is home to a wide variety of computing systems, including some of the most powerful high-performance computers in the world. These systems provide computing power to advance understanding in a broad range of disciplines. 

The EVS division seeks a post-doctoral appointee to develop an AI-enabled technology for collecting data on wildlife behavior around renewable energy facilities in support of the U.S. Department of Energy’s Solar Energy Technology Office. We seek a data scientist, who is passionate about machine/deep learning (ML/DL) algorithm development using images and video footage, interested in working with AI-enabled edge-computing cameras, and values interacting with experts in diverse disciplines. The successful candidate will develop vision-based ML/DL algorithms/models – which includes training data collection, ML/DL model training and testing, supporting software development, and hardware-software integration – for near real-time monitoring of bird interactions with solar energy infrastructure using AI-enable edge-computing cameras deployable at operational large-scale solar energy facilities.

Position Requirements

  • PhD in Computer Science, Environmental Science, Biology, or similar.
  • Experience in machine/deep learning, computer vision, scientific computing or mathematical optimization.
  • Programming experience in C, C++, and/or Python.
  • Good skills in sustainable software engineering practices such as version control, self-documenting code, unit testing and continuous integration.
  • Contributions to community software packages aligned with the position will be looked on favorably.
  • Good communication skills, both verbal and written.

Desirable Knowledge and Skills

  • Experience in applying machine/deep learning approach for ecological/environmental research.
  • Experience in Keras, Tensorflow, PyTorch, Chainer, or similar packages.
  • Ability to understand and implement methods from latest machine learning articles.
  • Experience and skills in interdisciplinary research involving computer scientists and discipline scientists.
  • Experience with OpenCV.
  • Experience with parallel programming such as MPI.
  • Experience in high-performance computing.
  • Collaborative skills including the ability to work well with other laboratories and universities, supercomputer centers, and industry.
  • Being open-minded and ability to acquire new skill set and explore new techniques to advance sciences.

As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1. You will be asked to disclose any such participation in the application phase for review by Argonne’s Legal Department.



Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.


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