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Computational Protein Design - Postdoctoral Researcher

Entry Level | Full-time
Engineering | livermore, CA | 06/19/2024

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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 important for continued success of the Laboratory’s mission.

Pay Range:

$112,800- $124,596

Please note that the pay range information is a general guideline only. Many factors are taken into consideration when setting starting pay including education, experience, the external labor market, and internal equity.

Job Description

We have multiple openings for Postdoctoral Researchers to join our interdisciplinary team of  Computational Bioengineers who will conduct research leading to our next-generation, machine learning-driven computational pipeline for protein design and optimizing protein-protein interactions as part of the Center for Predictive Bioresilience (CPB). CPB is an exciting and fast-paced engineering center combining predictive computational modeling, machine learning, and experimental biology to develop medical countermeasures.

You will work within a multi-disciplinary team with computational expertise in machine learning (ML), molecular simulation, optimization, and protein structure bioinformatics, and interface with our experimental team generating large datasets with novel high throughput assays aimed at informing predictive model development. You will leverage in-house computational tools and work to develop new machine-learning-based approaches and tools to design and optimize proteins (antibodies, immunogens, etc.) as therapeutics and vaccines. You will also work closely with an existing ML team to understand current capabilities and jointly develop a vision for development of next generation protein design models and tools. You will be team-oriented and have experience working in a team environment to achieve common goals. While supporting applied research projects, you will be provided mentorship, practical training and skill development to develop depth and breadth in machine learning techniques as well as gain exposure to a variety of application areas. These positions are in the Computational Engineering Division (CED) within the Engineering Directorate, matrixed to the Center for Predictive Bioresilience.

You will

  • Work closely with project scientists and engineers and participate in the evaluation and implementation of  computational frameworks (e.g., large language model-based) optimized for protein design tasks.
  • Contribute to the development of analysis methodologies; analyze data; document research through presentations and peer-reviewed journal articles.
  • Support technical activities for new capability development and technical problem solving.
  • Document methods and ensure quality standards for project deliverables.
  • Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings.
  • Travel as required to coordinate research with collaborators.
  • Perform other duties as assigned.

Qualifications

  • PhD in Machine Learning, Computational Biology, Statistics, Computer Science, Mathematics or a related field.
  • Fundamental knowledge and/or experience developing and applying algorithms in one or more of the following machine learning areas/tasks: protein structure machine learning, deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, transformer-based language modeling, multimodal learning, ensemble methods.
  • Experience developing and implementing deep learning models and algorithms using modern software libraries such as PyTorch, TensorFlow, or similar as evidenced through publications or software releases.
  • Experience working with protein structures and domain knowledge in bioinformatics and protein structure modeling sufficient to communicate effectively with team members.
  • Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions.
  • Sufficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.
  • Ability to travel.

Qualifications We Desire

  • Ability to secure and maintain a U.S. DOE Q-level security clearance, which requires U.S. Citizenship.
  • Strong understanding of protein structure bioinformatics and/or protein structure prediction.
  • Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflow.

Additional Information

#LI-Hybrid

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

This position requires either no security clearance, or a Department of Energy (DOE) L-level or Q-level clearance depending on the particular assignment.  

If you are selected and a security clearance is required, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing.  L and Q-level clearances require U.S. citizenship.  

If no security clearance is required, but 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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