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Computational Bioengineering Specialist
2 months ago
Company Overview
At Lawrence Livermore National Laboratory (LLNL), we are dedicated to enhancing the security of the United States through innovative research and development. Our team comprises some of the brightest minds in the field, committed to creating impactful solutions that contribute to a better world.
We prioritize a diverse and inclusive workforce, recognizing that a variety of perspectives and experiences are essential for our success.
Compensation Range:
$112,800 - $124,596
Please note that this pay range serves as a general guideline, influenced by various factors including education, experience, and market conditions.
Position Overview
We are seeking multiple Postdoctoral Researchers to become integral members of our interdisciplinary team focused on Computational Bioengineering. The successful candidates will engage in pioneering research aimed at developing our next-generation computational pipeline for protein design, particularly in optimizing protein-protein interactions as part of the Center for Predictive Bioresilience (CPB).
In this role, you will collaborate with a diverse team of experts in machine learning, molecular simulation, optimization, and protein structure bioinformatics. You will also work closely with experimental teams to analyze large datasets generated from novel high-throughput assays, which will inform the development of predictive models.
Key Responsibilities
- Collaborate with project scientists and engineers to evaluate and implement computational frameworks tailored for protein design tasks.
- Contribute to the development of analytical methodologies; perform data analysis; and document research findings through presentations and peer-reviewed publications.
- Support technical initiatives for new capability development and problem-solving.
- Ensure quality standards for project deliverables through meticulous documentation of methods.
- Publish research outcomes in reputable scientific journals and present findings at conferences and seminars.
- Travel as necessary to coordinate research efforts with collaborators.
- Perform additional duties as assigned.
Qualifications
- PhD in Machine Learning, Computational Biology, Statistics, Computer Science, Mathematics, or a related discipline.
- Proven experience in developing and applying algorithms in machine learning, particularly in protein structure analysis and deep learning.
- Demonstrated expertise in implementing deep learning models using contemporary software libraries such as PyTorch or TensorFlow.
- Familiarity with protein structures and a solid understanding of bioinformatics and protein modeling.
- Experience working within multidisciplinary teams to apply these capabilities in engineering contexts.
- Strong verbal and written communication skills for effective collaboration and presentation of technical information.
- Willingness to travel as required.
Preferred Qualifications
- Ability to obtain and maintain a U.S. DOE Q-level security clearance, requiring U.S. Citizenship.
- In-depth knowledge of protein structure bioinformatics and prediction techniques.
- Experience with high-performance computing and related methodologies.
Additional Information
This position is a Postdoctoral appointment with potential for extension up to three years, available to candidates who have completed their PhD by the time of hire.
Why Choose Lawrence Livermore National Laboratory?
- Recognized as one of the Best Places to Work by Glassdoor.
- Comprehensive benefits package.
- 401(k) plan.
- Relocation assistance available.
- Education reimbursement opportunities.
- Flexible work schedules based on project needs.
- Commitment to Inclusion, Diversity, Equity, and Accountability.
Security Clearance Requirements
This position may require a Department of Energy (DOE) L-level or Q-level security clearance, depending on the assignment.
Pre-Employment Drug Testing
Selected candidates must pass a pre-employment drug test, including testing for marijuana use in compliance with Federal Law.
Workplace Policies
LLNL is committed to maintaining a work environment free from discrimination and harassment, ensuring equal opportunity for all qualified applicants.
