Postdoctoral Researcher – Machine Learning for Protein Design (NREL)
Job posting number: #24026 (Ref:R10861)
This Job Posting is Expired.
Job Description
Posting Title
Postdoctoral Researcher – Machine Learning for Protein Design.
Location
CO - Golden.
Position Type
Postdoc (Fixed Term).
Hours Per Week
40.
Working at NREL
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.
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.
Job Description
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, and
- 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.
BEST Directorate
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Basic Qualifications
Must be a recent PhD graduate within the last three years.* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
- 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
Preferred Qualifications
- 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.
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Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Postdoctoral Researcher / Annual Salary Range: $71,300 - $117,600NREL 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 Summary
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 dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; and paid holidays. NREL employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement.* Based on eligibility rules
Drug Free Workplace
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.
Submission Guidelines
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.
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EEO Policy
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.
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