35 machine-learning positions at National Renewable Energy Laboratory NREL in United States
Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
to announce an exciting opportunity for a full-time Ph.D. intern with experience in machine learning, generative AI, foundation model, large language model, power system optimization, graphic neural network
-
enzyme activities and conduct directed evolution, structure-guided protein engineering, and machine learning-guided protein engineering studies to improve enzyme and pathway function. The ability
-
chemistry support to all research and development groups within the BEST directorate at NLR. To learn more about the research within this directorate, click here: https://www.nrel.gov/bioenergy . The team is
-
, and a competitive benefits package designed to support your career and well-being. Job Description The AI, Learning, and Intelligent Systems (ALIS) Group in the NLR Computational Science Center (CSC
-
development opportunities, and a competitive benefits package designed to support your career and well-being. Job Description The AI, Learning and Intelligent Systems (ALIS) Group in the NLR Computational
-
https://pubs.acs.org/doi/full/10.1021/acssuschemeng.5c0419 The successful candidate will be able to: Work safely and independently in a laboratory setting Learn new techniques and protocols Plan and
-
to use various computer software programs. Researcher III Relevant PhD. Or, relevant Master's Degree and 3 or more years of experience . Or, relevant Bachelor's Degree and 5 or more years of experience
-
/SpeedToPower What we can offer: A collaborative, fast-paced, flexible, and fun work environment Endless opportunities to both mentor and learn from experienced professionals in renewable and efficient energy
-
development for system baseline configuration and configuration management. You will work with the team to develop, maintain, and implement policy and procedure documents related to security. To learn more
-
closeout including turnover to end user/operations and disposition of documents, records and materials/equipment. Conducts evaluations and documents lessons learned that can be applied to future NLR projects