Postdoctoral Researcher – Machine Learning Protein Design

Pay $71300.00 - $117600.00 / year

Employment type

Full-Time

• Req#: R10861
Posting Title
• Postdoctoral Researcher – Machine Learning for Protein Design
Location
• CO - Golden
Position Type
• Postdoc (Fixed Term)
Hours Per Week
• 40

The National Renewable Energy Laboratory (NREL), located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for research and development of renewable energy and energy efficiency technologies.

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 eight 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.

A postdoctoral researcher role is available in NREL’s Renewable Resources and Enabling Sciences Center.

The successful candidate will work in the BOTTLE project to conduct bioinformatics and machine learning to select, engineer, and analyze protein biocatalysts for the deconstruction of polymer waste. This work will be done in close collaboration with a large, multi-disciplinary, multi-institutional team.

The successful candidate will be able to:

• work both independently and collaboratively as needed
• co-design the planning and execution of research with other researchers
• use state-of-the-art deep learning methods to develop predictive models with applications in protein and polymer science
• use machine learning techniques to analyze biochemical data to make engineering recommendations for improving desired molecular properties
• work with small experimental datasets, using techniques such as semi-supervised learning, transfer learning, and N-shot learning
• communicate scientific results effectively, both in written and oral formats
• author peer-reviewed publications
• work effectively in a large, multidisciplinary team of biologists, chemists, and engineers
• Maintain professionalism and an environment of mutual respect in all communication and interactions with fellow staff and collaborators.

Must be a recent PhD graduate within the last three years.

* Must meet educational requirements prior to employment start date.

• Troubleshooting and problem-solving skills, and attention to detail
• Ability to deliver high-quality results within aggressive timelines
• Strong record of quality peer-reviewed publications

• Research experience in machine learning, deep learning, and bioinformatics.
• Relevant experience in bioinformatics of esterase and other plastics-related enzymes.
• Experience developing approaches to select for and engineer thermo-tolerant enzymes.
• Demonstrated experience in Python and/or other relevant programming languages.

Job Profile:
Postdoctoral Researcher / Annual Salary Range: $71,300 - $117,600

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.

Benefits include medical, dental, and vision insurance; short-term disability insurance*; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and…