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Computational Biophysicist - Postdoctoral Researcher

Entry Level | Full-time
Physical Life Sciences | livermore, CA | 01/31/2024

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Company Description

Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory’s mission.

Pay Range:

$108,840.00 Annually

Job Description

NOTE: This is a two-year term appointment with the possibility of extension to a maximum of three years.

We have an opening for a highly motivated Postdoctoral Researcher to conduct research in computational biophysics and simulation, specifically with expertise in molecular dynamics simulations, enhanced sampling of rare events, machine learning, statistical analysis of molecular dynamics simulations and software development. You will be an integral member of an interdisciplinary team working with other national laboratories and companies.  You will be responsible for developing new software algorithms, writing code, understanding the requirements for each simulation campaign, and creating innovative analysis tools.  You will work with a team of computational biologists, physicists, material scientists, experimental biologist and computer scientists to create a novel machine-learned capability for modeling the conformational dynamics of protein complexes involved in cellular signaling pathways. This position is in the Biochemical and Biophysical Systems group of the Biosciences and Biotechnology Division.

You will:

  • Conduct advanced independent research to create a novel high performance computing capability for predicting the binding affinities and kinetics of protein-protein interactions at the atomistic and coarse-grained levels.
  • Contribute to the software development of high-performance computing tools for robust calculations of binding free-energies and kinetics.
  • Develop novel machine-learning based path-sampling methods for estimating protein binding rates and free energies.
  • Develop new workflows to analyze and visualize results from complex and large-scale molecular dynamics datasets.
  • Develop collaborations with external partners (Universities, Industry, other National Laboratories) to advance computational biology simulation efforts.
  • Prepare complex and detailed weekly progress reports to support project needs and deadlines. Prepare complex written analyses and verbal briefings, and present research results at scientific meetings.
  • Develop new and innovative research methods relevant to the needs of Laboratory programs and/or external funding agencies and interact with senior project staff and management to influence programmatic decisions.
  • Write proposals, secure funding, and establish independent research projects.

Qualifications

  • PhD in computer science, computational biology, computational physics, computational chemistry or equivalent combination of education and related experience.
  • Knowledge and experience in developing novel machine-learning based methods for enhancing the sampling of rare events, using free energy methods to model protein-protein binding affinities and developing statistical analysis of large-scale molecular dynamics datasets.
  • Experience at the postdoctoral or higher level in the fields of molecular dynamics simulations, free energy calculations, transition path theory, enhanced sampling methods, machine learning, and statistical mechanics.
  • Demonstrate advanced computer skills including programming experience with Python or C++ in a UNIX environment as well as experience using large high-performance computing clusters, including the use of job schedulers such as SLURM, PBS or Flux.
  • Ability to work independently on defined research projects, as well as a member of a large team. 
  • Ability to develop independent research projects as demonstrated through publication of peer-reviewed manuscripts in the field of molecular modeling and simulations.
  • Ability to travel, as necessary, to interact with sponsors, customers and collaborators.
  • Proficient written, verbal communication and interpersonal skills necessary to deliver presentations, prepare written reports and to interact with a diverse set of scientists, engineers, and other technical and administrative staff.

Qualifications We Desire:

  • Experience in collaborating with experimental biologists as well as understanding and using experimental data in combination with computational research.
  • Experience in developing and training machine-learning based models in high-performance computing systems.  
  • Experience computing binding affinity, stability and/or other metrics using scoring functions like Rosetta.
  • Experience with parallel programming tools used to develop high performance code on GPU’s and/or CPU’s, such as OpenMP, MPI, CUDA or OpenCL.
  • Experience using collaborative programming workflows and tools such as git, Gitlab, or subversion.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.

Why Lawrence Livermore National Laboratory?

Security Clearance

None required.  However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process.  This process includes completing an online background investigation form and receiving approval of the background check.  (This process does not apply to foreign nationals.) 

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.

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