Posting Title: Postdoctoral Researcher – Molecular Modeling and Machine Learning for Plant Biopolymers
Location: CO - Golden
Position Type: Postdoc (Fixed Term)
Hours Per Week: 40
COVID-19 Safety Protocols: Employment at NREL is contingent upon your compliance with all NREL and U.S. Department of Energy (DOE) safety protocols and mitigation efforts directed at the COVID-19 pandemic.
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.
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Job Description
The Renewable Resources and Enabling Sciences Center is a talented team of scientists (researchers) and technicians working in biological, chemical, and catalytic research approaches to renewable energy and materials for a circular economy. The center has strong focus in polymer design and upcycling, separations, synthetic biology and bioconversion, analytical sciences, computational modeling, and lignocellulosic chemistry and catalysis. Join our research team to develop and apply cutting edge simulation techniques to solve physicochemical research challenges towards a sustainable future.
Applicants are invited to apply for a postdoctoral position to apply cutting edge molecular simulation techniques (QM, MD, and QM/MM) to understand the structure, function, and interaction of complex polysaccharides in the plant cell wall (PCW). The position is part of larger efforts focused on understanding the three-dimensional structure of complex carbohydrate biopolymers, their mechanisms of cross-linking, and their function in the PCW.
This position also requires the candidate to be involved in developing and applying machine learning (Classifier models/Deep Learning) techniques to understand and decode substrate specificities of enzymes involved in the biosynthesis of complex carbohydrates in plants. This project will leverage specific high-throughput biochemical experimental datasets of glycosyl transferase structure, substrate specificity, and activity generated by our experimental collaborators.
This position will involve close collaboration with experimentalists utilizing NMR, chemical biology, and mass spectrometry to characterize carbohydrate bio-polymer structure and function and the development of biochemical experimental datasets on glycosyl transferases.
In addition, the position will have opportunities to support other research efforts within the Renewable Resources and Enabling Sciences Center. This is a very passionate and growing research center with mission driven team members who are highly skilled, diverse, and dynamic.
Job Responsibilities Include:
- Design and execute quantum mechanical calculations to estimate the energetics and thermodynamics of cross-linking reaction mechanisms in complex carbohydrate bio-polymers.
- Develop high-throughput in silico approaches to accurately estimate NMR chemical shifts of carbohydrate polymers.
- Design and execute molecular dynamics simulations of complex carbohydrate molecules (e.g. pectins) to characterize their 3D structure and develop structural correlations to their crosslinking ability.
- Perform protein structure prediction and docking studies to develop 3D structures of enzymes and enzyme-substrate complexes.
- Develop, apply, and benchmark interpretable machine learning and deep learning models trained on physics-based in silico data (protein structures, docking data, etc.) and experimental biochemical data to decode substrate specificity of glycosyl transferase enzymes.
- Transform simulation outputs and data into a form that can be compared against experimental results. Analyze results and provide conclusions and insight to the project team.
- Effectively communicate and interact with scientists and engineers to define the requirements of the simulations and models. Obtain necessary input data for simulations and provide meaningful interpretation of modeling results to guide experiments, operations, and engineering designs.
- Disseminate research findings to the community through peer-reviewed journal articles, presentations at conferences, symposia, and review meetings.
- Collaborate with modeling and experimental researchers at NREL and other institutions to discuss and analyze project results and propose new directions.
- Maintain professionalism and an environment of mutual respect in all communication and interactions with fellow staff and collaborators.
Basic Qualifications
Must be a Ph. D. graduate within the last 3 years in Chemistry, Physical chemistry, Computational chemistry, Chemical Engineering or a related field with a focus on computational modeling.
- Must meet educational requirements prior to employment start date.
Additional Required Qualifications
- Creativity in working with management, principal investigators, and senior staff to plan, design, and execute projects.
- A strong publication history in peer-reviewed scientific literature.
- Experience communicating research results at national/international conferences.
- Ability to work independently and in teams to deliver high-quality results within aggressive timelines.
- Experience with high performance computing, linux shells, and (preferred) GPU usage.
Preferred Qualifications
- Well-versed in molecular dynamics simulations best practices, forcefields, and packages (e.g. CHARMM, AMBER, GROMACS, NAMD etc.). Analysis of large-scale MD datasets of polymeric systems to characterize 3D structure and assembly is desired.
- Demonstrated expertise of applying quantum mechanical methods to estimate reaction thermodynamics, reaction energetics, kinetic rates, NMR chemical shifts, geometry optimizations and potential energy surfaces. Familiarity with Gaussian or any open source QM packages (psi4, pySCF) is desired.
- Expertise in state-of-the-art protein structure prediction methods and docking algorithms is also desired.
- Experience of developing machine learning models trained on experimental of physics-based simulation data is highly desired.
- Basic (or advanced) knowledge of organic, carbohydrate chemistry and/or polymer physics.
- Fluency in Python/BASH.
Annual Salary Range
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 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
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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