Find Jobs

.

.

.

.

From day one at NREL, you’ll connect with coworkers driven by the same mission to save the planet. By joining an organization that values a supportive, inclusive, and flexible work environment, you’ll have the opportunity to engage through our ten employee resource groups, numerous employee-driven clubs, and learning and professional development classes.

NREL supports inclusive, diverse, and unbiased hiring practices that promote creativity and innovation. By collaborating with organizations that focus on diverse talent pools, reaching out to underrepresented demographics, and providing an inclusive application and interview process, our Talent Acquisition team aims to hear all voices equally. We strive to attract a highly diverse workforce and create a culture where every employee feels welcomed and respected and they can be their authentic selves.

Our planet needs us! Learn about NREL’s critical objectives, and see how NREL is focused on saving the planet.

Note: Research suggests that potential job seekers may self-select out of opportunities if they don't meet 100% of the job requirements. We encourage anyone who is interested in this opportunity to apply. We seek dedicated people who believe they have the skills and ambition to succeed at NREL to apply for this role.

The Renewable Resources and Enabling Sciences Center is a talented team of scientists and technicians working in biological, chemical, and catalytic research approaches to renewable energy and materials for a circular economy. The center has strong thrusts in polymer design and upcycling, separations, synthetic biology and bioconversion, analytical sciences, computational modeling, and lignocellulosic chemistry and catalysis.

A postdoctoral researcher role is available in NREL’s Renewable Resources and Enabling Sciences Center. The successful candidate will develop machine learning and deep learning tools that are able to identify and design process-advantaged enzymes for the deconstruction of polymer waste, conversion of C1 substrates, biosensor design, and use in metabolic pathways. This work will be done in close collaboration with a large, multi-disciplinary, multi-institutional team.

The successful candidate will be able to:

• co-design the planning and execution of protein selection, design, and engineering efforts with other researchers

• use state-of-the-art deep learning methods to develop predictive models with applications in enzyme selection, engineering, and design

• use machine learning techniques to analyze biochemical data to make engineering recommendations for improving desired enzyme properties

• work with small experimental datasets, using techniques such as semi-supervised learning, transfer learning, etc.

• use structural information, bioinformatics, molecular modeling, and / or machine learning techniques to develop protein sequence/structure/function relationships and make engineering recommendations for improving desired enzyme properties

• work effectively both independently and in a large, multidisciplinary, multi-institutional team of biologists, chemists, and engineers.

• collaborate with modeling and experimental collaborators to plan, execute, discuss, and analyze project results and propose new directions.

• communicate scientific results effectively, both in written and oral formats

• author peer-reviewed publications

• maintain professionalism and an environment of mutual respect in all communication and interactions with fellow staff and collaborators

.

* Must meet educational requirements prior to employment start date.

• Research experience in machine learning, deep learning, and bioinformatics
• Troubleshooting skills, problem-solving skills, and attention to detail
• Ability to deliver high-quality results within aggressive timelines
• A strong publication history in the peer-reviewed scientific literature

• Experience developing approaches to select for and engineer thermo-tolerant enzymes
• Relevant experience with molecular dynamics simulations

• Demonstrated experience in Python and/or other relevant programming languages, especially applied to the development of high-throughput computational workflows

.

The anticipated closing window for application submission is up to 30 days and may be extended as needed.

NREL takes into consideration a candidate’s education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions.

* Based on eligibility rules

NREL is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.

If you are offered employment at NREL, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.

Please note that in order to be considered an applicant for any position at NREL you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.

.

NREL is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

EEO is the Law | Pay Transparency Nondiscrimination | Reasonable Accommodations

E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.